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diff --git a/docs/index.html b/docs/index.html
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-<!-- desc(5A0113B34292)[max=175]:posts/2023-11-20/index.html -->
+Hey folks, welcome back to another exciting R programming journey! Today, we’re diving into the fascinating world of exponential regression using base R.…
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+In the realm of data analysis, quadratic regression emerges as a powerful tool for uncovering the hidden patterns within datasets that exhibit non-linear relationships.…
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+My R package <code>{healthyR.ts}</code> has been updated to version 0.3.0; you can install it from either CRAN, r-universe or GitHub. Let’s go over some of the changes and improvements.
 </div>
 </a>
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+Multiple linear regression is a powerful statistical method that allows us to examine the relationship between a dependent variable and multiple independent variables.
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+Regression models are a powerful tool for predicting future values based on historical data. They are used in a wide…<code></code>
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+Prediction intervals are a powerful tool for understanding the uncertainty of your predictions. They allow you to specify a range of values within which you are…
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+In the realm of statistics, a cumulative distribution function (CDF) serves as a crucial tool for understanding the behavior of data. It provides a comprehensive picture of…
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+If you’re an R enthusiast like me, you know that data manipulation is at the core of everything we do. The ability to transform your data swiftly…<code></code>
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+The gamma distribution is a continuous probability distribution that is often used to model waiting times or other positively…
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+As an R programmer and enthusiast, I’m excited to delve into the fascinating world of probability distributions. One…
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+The multinomial distribution is a…
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+Randomness is an essential part of many statistical and machine learning tasks. In R, there are a number of functions that can be used to generate random numbers, but the <code>ru…</code>
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+A log-log plot is a type of graph where both the x-axis and y-axis are in logarithmic scales. This is particularly useful when…
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+Logistic regression is a statistical method used for predicting the probability of a binary outcome. It’s a fundamental tool in machine learning and statistics, often…
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+Before we dive into the code, let’s briefly understand what a Bland-Altman plot is. It’s a graphical method to visualize the agreement between two measurement techniques…
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+A scree plot is a line plot that shows the…
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+<p><a href="./posts/2023-10-23/index.html"> <p class="card-img-top"><img src="posts\2023-10-23\index_files\figure-html\ggplot2_bubble_chart-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Bubble charts are a great way to visualize data with three…
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+A Pareto chart is a type of bar chart that shows the frequency of different categories in a…
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+In the world of data analysis, uncovering hidden relationships between variables is often the key to making informed decisions. Interaction plots in R can be your secret…
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+When working with time series data, one common challenge is…<code></code>
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+Hey there, R enthusiasts! Today, we’re going to dive into the fascinating world of time series analysis using the <code>ts_adf_test()</code> function from the <code>healthyR.ts</code> R library. If you’re into data, statistics, and R coding, this is a must-know…
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+Time series data is essential for understanding trends and making forecasts in…<code></code><code></code>
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+As…
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+Let’s dive into the world of R and explore how to use <code>cex</code> to change the size of plot elements in base R. Whether you’re a seasoned R user or just starting out, understanding how to control the size of text and symbols in your…
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+Creating a horizontal legend in base R can be a useful skill when you want to label multiple categories in a…
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+Changing the size of the legend on a plot in R can be a handy skill, especially when you want to enhance the readability and aesthetics of your visualizations. In this blog…
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+Legends are an essential part of data visualization. They help us understand the meaning behind the colors and shapes in our plots. But what if your legend is too big or…
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+As an R programmer, you may want to create added variable plots to…<code></code><code></code>
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+Stacked dot plots are a type of plot that displays frequencies using dots, piled one over the other. In R, there are several ways to create stacked…
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+Radar charts, also known as spider, web, polar, or star plots, are a useful…
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+Boxplots are a great way…
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+Decision trees are a powerful machine learning algorithm that can be…
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+Boxplots are a great way to visualize the distribution of a dataset. However, sometimes the default ordering of boxplots may not be ideal for the data being presented. In…
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+Data visualization is a crucial aspect of data analysis and exploration. It allows us to gain insights, spot trends, and communicate our findings effectively. In R…
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+Data visualization is a crucial tool in the data scientist’s toolkit. It allows us to explore and communicate complex patterns and…<code></code>
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+Data visualization is a crucial tool in data analysis, allowing us to gain insights from our data quickly. One of the fundamental techniques for exploring relationships…
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+Linear regression is a fundamental statistical technique used to model the relationship between a dependent variable and one or more independent variables. While fitting a…
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+Data visualization is a powerful tool in a data scientist’s toolkit. It not only helps us understand our data but also presents it in a way that is easy to comprehend. In…
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+Data visualization is a powerful tool for gaining insights from your data. Scatter plots, in particular, are excellent for visualizing relationships between two continuous…
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+Histograms are a fundamental tool in data analysis and visualization, allowing us to explore the distribution of data quickly and effectively. While creating a histogram in…
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+Histograms are powerful tools for visualizing the distribution of a single variable, but what if you want to compare the distributions of…
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+Histograms are a fantastic way to visualize the distribution of data. They provide insights into the underlying patterns and help us understand our data better. But what if…
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+Data visualization is a crucial aspect of data analysis. In R, the flexibility and power of its plotting capabilities allow you to create compelling visualizations. One…<code></code><code></code><code></code><code></code>
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+If you’re an R…<code></code><code></code>
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+Support Vector Machines (SVM) are a powerful tool in the world of machine learning and classification. They excel in finding the optimal decision boundary between…<code></code>
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+Are you interested in visualizing demographic data in a unique and insightful way? Population pyramids are a fantastic tool for this purpose! They allow you to compare the…
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+Data visualization is a powerful tool for gaining insights from your data. In R, you have a plethora of libraries and functions at your disposal to create stunning and…
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+When it comes to analyzing multivariate data, Principal Component Analysis (PCA) is a powerful technique that can help us uncover hidden patterns, reduce dimensionality, and…<code></code><code></code>
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+As an R programmer, one of the most useful functions to know is the jitter function. The jitter function is used to add random noise to a numeric vector, which can be…
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+Kernel Density Plots are a type of plot that displays the distribution of values in a dataset using one continuous curve. They are similar to histograms, but they are even…
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+When it comes to conveying…<strong></strong><code></code>
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+Data visualization is a powerful tool for understanding the relationships between variables in a dataset.…<code></code><code></code>
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+Categorical data is a type of data that represents distinct groups or categories. Visualizing categorical data can provide valuable insights and help in understanding…
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+Are you tired of looking at plain, vanilla histograms that just show the distribution of your data without any additional context? If so, you’re in for a treat! In this blog…
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+Histograms are a powerful tool for visualizing the distribution of numerical data. They allow us to quickly understand the frequency distribution of values within a dataset.…
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+Graphs…<code></code><code></code>
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+Understanding the distribution of your data is a fundamental step in any data analysis process. It…<code></code><code></code><code></code>
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+Data visualization is a powerful tool that allows us to uncover patterns and insights within datasets. One such tool in the R programming arsenal is the <code>stripchart()</code> function. If you’re looking to reveal distribution patterns in your data with style and simplicity, then this function might just become your new best friend. In this blog…<code></code>
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+Data visualization is a powerful tool for understanding and interpreting data. In this blog post, we will explore how to create…
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+Are you ready to dive into the world of data visualization in R? One powerful tool at your disposal is the box plot, also known as a box-and-whisker plot. This versatile…<code></code><code></code>
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+Are you tired of dealing with irregularly spaced data points that just don’t seem to fit together? Do you find…<code></code>
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+In the vast world…<code></code><code></code>
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+In mathematical modeling and data analysis, it is often necessary to solve systems of equations to find the values of unknown variables. R provides the <code>solve()</code> function, which is a powerful tool for solving systems of linear equations. In this blog post, we will explore the purpose of solving systems of equations, explain…<code></code>
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+The <code>substring()</code> function in R is used to extract a substring from a character vector. The syntax of the function is:
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+Title: Unleashing the Power of pmax() and pmin() Functions in R
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+As data-driven decision-making becomes more critical in various fields, the ability to extract valuable insights from datasets has never been more important. One common task…<code></code>
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+When it comes to data visualization in R, the <code>par()</code> function is an indispensable tool that often goes overlooked. This function allows you to control various…<code></code>
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+Data analysis often requires preprocessing and transforming data to make it more suitable for analysis. In R, the <code>scale()</code> function is a powerful tool that allows you to standardize or normalize your data, helping you unlock deeper…<code></code><code></code>
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+As a programmer, you’re well aware of the importance of data…<code></code><code></code>
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+Welcome, fellow data enthusiasts, to another exciting blog post! Today, we’re diving deep into R’s invaluable <code>str()</code> function – a powerful tool for gaining insight into your datasets.…<code></code><code></code>
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+Welcome, data enthusiasts! If you’re diving into the realm of data analysis with R, one function you’ll undoubtedly encounter is <code>read.delim()</code>. It’s an essential tool that allows you to read tabular data from a delimited text file and load it into R for further analysis. But fret not, dear reader, as I’ll walk you…
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+Hey fellow R enthusiasts!
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+Welcome, fellow programmers, to this exciting journey into the world of R functions! Today, we’ll explore four powerful functions: <code>get()</code>, <code>get0()</code>, <code>dynGet()</code>, and <code>mget()</code>. These functions may sound mysterious, but fear not; we’ll demystify them together and see how they can be incredibly handy tools in your R toolkit. So…
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+As a programmer, you must have encountered situations where you need…<code></code>
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+Welcome to another exciting blog post where we delve into the world of R programming. Today, we’ll be discussing the <code>intersect()</code> function, a handy tool that helps us find the common elements shared between two or more vectors in R. Whether you’re a seasoned R programmer or just starting your journey…
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+As data-driven decision-making continues to shape our world, the need for insightful statistical analysis becomes ever more apparent. One crucial tool in a programmer’s…
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+…<code></code><code></code><code></code><code></code>
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+As a programmer and data enthusiast, you know that summarizing data is essential to gain insights into its distribution and…<code></code><code></code>
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+Calculating percentages by group is a common task in data analysis. It allows you to understand the distribution of data within different categories. In this blog post…
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+As a…<code></code><code></code>
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+If you’ve been working with R for some time…<code></code><code></code><code></code><code></code>
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+If you’re an aspiring data scientist or R programmer, you must be familiar with the powerful data structure called “lists.” Lists in R are collections of…
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+In data analysis and manipulation tasks, it’s common to encounter situations where we need to identify and handle duplicate rows in a dataset. In this blog post, we…<code></code>
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+In data analysis and programming, it’s common to encounter situations where you need to identify duplicate values within a dataset. Whether you’re a beginner or an…
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+In the…<code></code><code></code>
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+As a programmer, you’ll often come…<code></code><code></code>
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+As a programmer, working with data is a crucial aspect of our work. In R, there are numerous functions available that simplify data analysis tasks. One such function is <code>col…</code><code></code>
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+In the realm of programming, R is a widely-used language for statistical computing and data analysis. Within R, there exists a powerful function called <code>identical()</code> that allows programmers to compare objects for exact equality. In this blog post, we will delve into the syntax and…<code></code>
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+Managing files is an essential task for any programmer, and when working with R, the <code>file.rename()</code> function can…<code></code><code></code>
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+Using a Windows .bat file to execute an R script can be a convenient way to automate tasks and…
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+In the world of data analysis, time-series data is a common sight. Whether it’s stock prices, weather patterns, or website traffic, understanding the relationship between…<code></code>
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+In the world of data analysis and statistics, grouping data based on certain criteria is a common task. Whether you’re working with large datasets or analyzing trends…<code></code>
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+Welcome to the world of data visualization in R! In this blog post, we will explore the <code>abline()</code> function, a versatile tool that allows you to add straight lines to your plots…<code></code>
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+Bootstrap resampling is a powerful technique used in statistics and data analysis to estimate the uncertainty of a statistic by repeatedly sampling from the original data.…
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+As a…<code></code><code></code><code></code>
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+Sampling is a fundamental technique in data analysis and…<code></code><code></code>
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+As a programmer, you’re constantly faced with the task of organizing and analyzing…<code></code><code></code>
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+As a programmer, it’s crucial to have a deep…<code></code><code></code>
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+The <code>lm()</code> function in R is used…
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+The <code>formula()</code> function in R is a generic function that…
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+As a programmer, you may come across various scenarios where you need to create complex model formulas in R. However, constructing these…<code></code>
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+In R, the <code>file.info()</code> function is a useful tool for retrieving file information, such as file…<code></code>
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+In the world of data analysis and manipulation, tidying and reshaping data is often an essential step. R’s <code>tidyr</code> library provides powerful tools…<code></code><code></code>
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+In the realm of data analysis and programming…<code></code><code></code><code></code>
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+As a programmer, you’re always on the lookout for tools that can enhance your productivity and make your code more efficient. In the world of R programming, the <code>do.call()</code> function is one such gem. This often-overlooked function is a powerful tool that allows you to dynamically call other functions, opening up a world of possibilities for…<code></code>
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+Regular expressions, often abbreviated as regex, are powerful tools used in programming to match and manipulate text patterns. While they might seem intimidating at first…
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+Programming is often about making decisions based on certain conditions. In the world of R, there are numerous functions that can help us simplify our code and make it more…
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+When working with data, it is important to be aware of the file size of…
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+In the realm of data analysis and manipulation, R has become a popular programming language due to its extensive collection of packages and libraries. One common task…<code></code><code></code><code></code>
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+Yesterday I had the need to see data that had a grouping column in it. I wanted to use the <code>tidy_four_autoplot()</code> function on it from the <code>{TidyDensity}</code> library on it. This post will explain how I did it. The…<code></code>
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+The <code>sink()</code> function in R is…
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+To effectively extract insights and communicate findings, you need…<code></code><code></code>
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+When it comes to working with files in R, having a powerful tool at your disposal can make a world of difference. Enter the <code>list.files()</code> function, a versatile and handy utility that allows you to effortlessly navigate through directories, retrieve file names, and perform various file-related operations. In…<code></code>
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+As a…<code></code><code></code>
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+Formatting dates is an essential task in data analysis and programming. In R, there are…<code></code>
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+Dates and times are essential components in many programming tasks, and R provides various functions and packages to handle them…
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+Mother’s Day is a special occasion to honor and appreciate the incredible women in our lives. As programmers, we can use our coding skills to make our lives easier when it…
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+In this post, we will cover the basics of handling dates and times in R using the <code>as.Date</code>, <code>as.POSIXct</code>, and <code>as.POSIXlt</code> functions. We will use the example code…
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+<p><a href="./posts/rtip-2023-05-10/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-05-10\Capture.PNG"  class="thumbnail-image card-img"/></p> </a></p>
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+Yesterday I posted on using VBA to…
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+Today I am going to briefly go over an extremely simple example of running some R code via Excel VBA.
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+Introducing the Updated <code>{healthyR.data}</code> Package: Your Ultimate Health Data Companion
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+The code…
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+<p><a href="./posts/rtip-2023-05-04/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-05-04\Capture.PNG"  class="thumbnail-image card-img"/></p> </a></p>
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+The code is used to create a Shiny app that allows the user to search for…
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+The download.file() function in R is used to download files from the internet and save them onto your computer. Here’s a simple explanation of how to use it:
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+In this post, we are using a package called <code>tidymodels</code>, which provides a suite of tools for modeling and machine learning.
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+This is a Shiny app for building models using the <code>{tidyAML}</code> which is based on the <code>tidymodels</code> package in R. The app allows you to upload your own data or choose from one of two built-in datasets (mtcars or…
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+<p><a href="./posts/rtip-2023-04-27/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-27\1.PNG"  class="thumbnail-image card-img"/></p> </a></p>
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+As data science continues to be a sought-after field…<code></code><code></code><code></code>
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+<p><a href="./posts/rtip-2023-04-26/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-26\1.PNG"  class="thumbnail-image card-img"/></p> </a></p>
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+Yesterday I spoke about building <code>tidymodels</code> models using my package <code>{tidyAML}</code> and <code>{shiny}</code>. I have made an update to it, and will continue to make updates to it this week.
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+<p><a href="./posts/rtip-2023-04-25/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-25\1.PNG" alt="Initial Panel"  class="thumbnail-image card-img"/></p> </a></p>
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+Welcome to the <code>{tidyAML}</code> Model Builder, a Shiny web application that allows you to build predictive models using the <code>tidyAML</code> and Parsnip packages in R.
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+<p><a href="./posts/rtip-2023-04-24/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-24\Capture1.PNG"  class="thumbnail-image card-img"/></p> </a></p>
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+I have been writing about using the <code>{TidyDensity}</code> package with <code>shiny</code> for the last few posts, and…<code></code><code></code>
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+<p><a href="./posts/rtip-2023-04-21/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-21\InputData.PNG"  class="thumbnail-image card-img"/></p> </a></p>
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+If you’re new to data science or statistics, you may have heard about probability distributions. Probability distributions are mathematical functions that help us understand…
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+<p><a href="./posts/rtip-2023-04-20/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-20\DownloadData.PNG" alt="Download Buttong"  class="thumbnail-image card-img"/></p> </a></p>
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+In the previous post we allowed users to choose a distribution and a plot type. Now, we want to allow users to download a <strong>.csv</strong> file of the data that is generated.
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+<p><a href="./posts/rtip-2023-04-19/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-19\image.PNG" alt="TidyDensity with Shiny"  class="thumbnail-image card-img"/></p> </a></p>
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+Shiny is an R package that allows you to create interactive web applications from R code. In this blog post, we’ll…
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+<p><a href="./posts/rtip-2023-04-18/index.html"> <div class="listing-item-img-placeholder card-img-top" >&nbsp;</div> </a></p>
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+Shiny is an R package that allows you to build interactive web applications using R code. TidyDensity is an R package that provides a tidyverse-style…
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+<p><a href="./posts/rtip-2023-04-11/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-11\example.JPG"  class="thumbnail-image card-img"/></p> </a></p>
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+In the analytics realm whether some like it or not, Excel is huge and maybe King. This is due to the fact of the shear volume of people using it. Microsoft has positioned…
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+<p><a href="./posts/rtip-2023-04-07/index.html"> <div class="listing-item-img-placeholder card-img-top" >&nbsp;</div> </a></p>
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+Reading in an Excel file with multiple sheets can be a daunting task, especially for users who are not…
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+<p><a href="./posts/rtip-2023-04-06/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-04-06\brvm-logo.png"  class="thumbnail-image card-img"/></p> </a></p>
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+This R package provides a user-friendly interface for accessing data from the <code>{BRVM}</code>, which is a regional stock exchange serving multiple West African countries. With this package, users can easily retrieve historical stock price…
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+<p><a href="./posts/rtip-2023-04-05/index.html"> <div class="listing-item-img-placeholder card-img-top" >&nbsp;</div> </a></p>
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+In…<code></code><code></code>
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+In this blog post, we will be discussing how to create a Shiny application in R that will download…<code></code><code></code>
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+Time series analysis is a powerful…
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+Yesterday I posted on performing a benchmark on reading in a compressed <code>.csv.gz</code> file of a 2,000 by 2,000 <code>data.frame</code>. It was brought to my attention by someone on Mastadon (<span class="citation" data-cites="mariviere">@mariv…</span><span class="citation" data-cites="fediscience.org"></span><code></code><code></code>
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+I received an email over the weekend in regards to my last post not containing the reading in of <code>gz</code> compressed file(s) for the benchmarking. While this was not an over site per-se it was a…
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+I will demonstrate how to generate a 1,000 row and column matrix with random numbers in R, and then…
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+Cumulative mean is a statistical…
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+The CCI30 Crypto Index is a cryptocurrency index that tracks the…
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+I am thrilled to announce that the R universe of packages <code>{healthyverse}</code> has surpassed 60,000…
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+In this post I will talk about the use of the R functions <code>apply()</code>, <code>lapply()</code>, <code>sapply()</code>, <code>tapply()</code>, and <code>vapply()</code> with examples.
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+I had just recently posted on making an attempt to speedup computations with my package <code>{TidyDensity}</code> using a purely data.table solution, yes of course I can use <code>{dtplyr}</code> or <code>{tidytabl…</code>
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+If you live in New York and rely on heating oil to keep your home warm during the…
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+So I was challanged by Adrian Antico to learn <code>data.table</code>, so yesterday I started with a single function from my package <code>{TidyDensity}</code> called <strong>tidy_bernoulli()</strong>.
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+The <code>imap()</code> function is a powerful tool for iterating over a list or a vector while also keeping track of the index or names of…
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+The pmap()…
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+In this article, we will discuss how to perform an ARIMA forecast on nested data or data that is in a list using R programming language. This is a common scenario in which…
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+Are you tired of manually manipulating…<code></code><code></code><code></code><code></code>
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+When writing a function, it is possible that…<code></code><code></code>
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+There are many approaches to modeling time series data in R. One of the types of data that we might come across is a nested time series. This means the data is grouped…
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+There are many…<code></code>
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+In time series analysis, it is common to split the data into training and testing sets to…<code></code><code></code>
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+The <code>{tidyAML}</code> package…<code></code>
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+I’m excited to announce that the R package {tidyAML} is now officially available on CRAN! This package is designed to make it easy for users to perform automated machine…
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+Are you interested in visualizing time series data in a clear and concise way? The R package <code>{healthyR.ts}</code> provides a…<strong></strong>
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+Today I am going to make a short post on the R package <code>{box}</code> which was showcased to me quite nicely by <strong>Michael Miles</strong>. It was…<code></code>
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+Are you tired of spending hours tuning and testing different machine learning models for your regression or classification problems? The new R package <code>{tidyAML}</code> is here to simplify the process for you! tidyAML is a simple interface for automatic machine learning that fits the tidymodels framework, making it easier for you to solve…
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+Getting data for health care in the US can sometimes be hard. With my R package <code>{healthyR.data}</code> I am hoping to alleviate some of that pain.
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+I am almost ready for a first release of my R package <code>{tidyAML}</code>. The purpose of this is to act as a way of quickly generating models using the <strong>parsnip</strong> package and…<strong></strong><strong></strong><strong></strong><code></code>
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+When working in R I find it best to create a new project when working on something. This keeps all of the data and scripts in one location. This also means that if you are…
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+In R, lists are a fundamental data structure that allows us to store multiple objects of different data types under a single name. Often times, we want to extract certain…
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+If you’re looking for an easy-to-use package to calculate cumulative statistics in R, you may want to check out the TidyDensity package. This…
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+I am working on finishing up a few things with my new R package <code>{tidyAML}</code> before I release it to CRAN. One…<code></code><code></code><strong></strong>
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+A diverging lollipop chart is a useful tool for comparing data that falls into two categories, usually indicated by different colors.…
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+R is a powerful programming language that is widely used for data analysis, visualization, and machine learning. One of the features of R that makes it versatile and…
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+As we collect data over time, it’s important to look for patterns and trends that can help us understand what’s happening. One common way to do this is to look at the median…
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+Are you looking for a powerful and efficient library for time series analysis? Look no further than <code>{healthyR.ts}</code>! This library has recently been updated with new functions and improvements, making…
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+Healthcare data analysis can be a complex and time-consuming task, but it doesn’t have to be. Meet <code>{healthyR}</code>…<code></code>
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+Transforming data refers to the process of changing the…
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+The <code>{purrr}</code> package in R is a powerful tool for working with lists and other data structures. One particularly useful function in the package is <code>keep()</code>, which allows you to filter a list by keeping only the elements…
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+In the most basic sense for time series, a series is stationary if the properties of the generating process (the process that generates the data) do not change over time…
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+A time series is a set of data points collected at regular intervals of time. Sometimes, the data points in a time series change…
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+<p><a href="./posts/weekly-rtip-lists-2023-01-20/index.html"> <div class="listing-item-img-placeholder card-img-top" >&nbsp;</div> </a></p>
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+Manipulating lists in R is a powerful tool for organizing and analyzing data. Here are a few common ways to manipulate lists:
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+<p><a href="./posts/rtip-2023-01-19/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-01-19\ggplot-plot.png"  class="thumbnail-image card-img"/></p> </a></p>
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+XGBoost, short for “eXtreme Gradient Boosting,” is a powerful…
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+<p><a href="./posts/rtip-2023-01-18/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-01-18\index_files\figure-html\unnamed-chunk-4-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Geometric Brownian motion (GBM) is a widely used model in financial analysis for modeling the behavior of stock prices.…
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+<p><a href="./posts/rtip-2023-01-17/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-01-17\index_files\figure-html\unnamed-chunk-5-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Time series analysis is a crucial tool for forecasting and understanding trends in various industries, including finance, economics, and…<code></code>
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+<p><a href="./posts/rtip-2023-01-16/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-01-16\index_files\figure-html\unnamed-chunk-7-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Today’s post is going to center around the automatic k-means functionality of <code>{healthyR.ai}</code>. I am not going to get into what it is or how it works, but rather…<code></code><code></code>
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+Yesterday I posted on An Update to <code>{tidyAML}</code> where I was discussing some of my thought process and how things could potentially work for the package.
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+I have been doing a lot of work on a new package called <code>{tidyAML}</code>. <code>{tidyAML}</code> is a new R package that makes it easy to use the <code>{tidymodels}</code> ecosystem to perform automated machine learning (AutoML). This package provides a simple and intuitive interface that allows users to quickly generate machine learning…<code></code><code></code>
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+<p><a href="./posts/rtip-2023-01-11/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-01-11\index_files\figure-html\unnamed-chunk-3-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+A…
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+<p><a href="./posts/rtip-2023-01-10/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-01-10\index_files\figure-html\unnamed-chunk-4-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Histogram binning is a technique used in data visualization to group continuous data into a set of discrete bins, or intervals. The purpose of histogram binning is to…
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+Hello R users!
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+<p><a href="./posts/weekly-rtip-2023-01-06/index.html"> <p class="card-img-top"><img data-src="posts\weekly-rtip-2023-01-06\index_files\figure-html\unnamed-chunk-2-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Brownian motion, also known as the random motion of particles suspended in a fluid, is a phenomenon that was…
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+<p><a href="./posts/rtip-2023-01-05/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2023-01-05\index_files\figure-html\unnamed-chunk-4-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Random walks are a mathematical concept that have found various applications in fields such as economics, biology, and computer science. At a…
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+Calendar heatmaps are a useful visualization tool for…
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+Time-to-event analysis, also known as survival analysis, is a statistical technique used to analyze the length of time until an event occurs. This type of analysis is often…
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+The Gartner Magic Chart is a powerful tool for analyzing healthcare data and identifying trends and patterns that can inform decision making. It was…
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+Time series models are a powerful tool for forecasting future values…
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+I got a little bored one day and…
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+If you’re working with statistical distributions in R, you may be interested in the <code>{TidyDensity}</code> package. This package provides a set of functions for creating, manipulating, and…<code></code>
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+Random walks are a type of stochastic process that can be used to model the movement of a particle or system over time. At each time step, the position of the particle is…
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+In statistics, it is often useful to view different versions of the same…
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+Scedacity plots are a useful tool for evaluating the performance of time series models and identifying trends or patterns in the data. They are a type of…
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+The R package <code>{healthyR.ts}</code>, is an R package that allows users to easily plot and analyze their time series data. The package includes a variety of functions, but one of the standout features is the…
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+<code>{TidyDensity}</code> is an R package that provides tools for working with probability distributions in a tidy data format. One of the key functions in the package is <code>tidy_distribut…</code>
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+A mixture distribution is a type of probability distribution that is created by combining two or more simpler distributions. This allows us to model…
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+A Q-Q plot, or quantile-quantile plot, is a graphical tool for comparing two sets of data to assess whether they come from the same distribution. In the context of time…
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+One of the most important steps in data analysis is visualizing the distribution…
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+If you want to generate multiple <code>parsnip</code> model…<code></code>
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+<p><a href="./posts/rtip-2022-12-06/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2022-12-06\index_files\figure-html\example2-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Sometimes one may find it useful or necessary to scale their data during a modeling or analysis phase. One of these such transformations is the z-score scaling.
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+Many times when we are working with a data set we will want to break it up into groups and place them into a list and work with them…<code></code>
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+Minimal coding ML is not something that is unheard of and is rather prolific, think <code>h2o</code> and <code>pycaret</code> just to name two. There is also no shortage available for <code>R</code> with the <code>h2o</code> interface…<code></code><code></code><code></code>
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+When working with the <code>{tidymodels}</code> framework there are ways to pull model metrics from a <code>workflow</code>, since <code>{healthyR.ai}</code> is built on and around the <code>{tidyverse}</code> and <code>{tidymodels}</code> we can do the same. This post will focus on the…<code></code>
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+Ge…<code></code><code></code>
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+In <strong>R</strong> there are many times where we will work with <em>lists</em>. I won’t go into why lists are great or really the structure of a list but rather simply working with them.
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+When modeling it is always good to understand your model performance against some metric The <code>{tidymodels}</code> <code>package</code> <code>{yardstick}</code> is a great resource for this.
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+Many times someone may want to see a summary or cumulative statistic for a given set of data or even from several simulations of data. I went over bootstrap plotting earlier this month, and this is a form of what we will go over today although slightly more…
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+A large portion of data modeling occurrs not only in the data cleaning phase but also in the <em>data preprocessing</em> phase. This can include things like <em>scaling</em> or <em>normalizing</em> data before proceeding to the modeling phase. I will discuss one such function…<em></em><code></code><code></code>
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+I have previously written about bootstrap modeling with <code>{purrr} and {modelr}</code> here. What if you would like to do some simple <strong>bootstrap</strong> modeling <em>without</em> importing a…
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+<p><a href="./posts/weekly-rtip-update-2022-11-18/index.html"> <p class="card-img-top"><img data-src="posts\weekly-rtip-update-2022-11-18\tidydensity.png"  class="thumbnail-image card-img"/></p> </a></p>
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+I have made several updates to <code>{healthyverse}</code>, this has resulted in new releases to CRAN for <code>{healthyR.ai}</code>, <code>{healthyR.ts}</code>, and <code>{TidyDesnsity}</code>.
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+<p><a href="./posts/rtip-2022-11-17/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2022-11-17\index_files\figure-html\viz-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Many times in modeling we want to get the uncertainty in the model, well, bootstrapping to the rescue!
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+There can be times in which you may want to see a cumulative statistic, maybe in this particular case it is the harmonic mean. Well with the <code>{TidyDensity}</code> it is possible…<code></code>
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+Sometimes we may want to…
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+Sometimes we may want to quickly find skewed features in a data set. This is easily achiveable using the <code>{healthyR.ai}</code> library. There is a simple function called <code>hai_ske…</code>
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+In time series analysis there is something called a lag. This simply means we take a look at some past event from some point in time <em>t</em>. This is a non-statistical method for looking at a…
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+There may be times when you have multiple structured files in the same folder, maybe they are <code>.csv</code> files. For this short tip, we will say that they are.
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+K-Means is a clustering algorithm that can be used to find potential clusters in your data.
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+<p><a href="./posts/rtip-2022-11-08/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2022-11-08\index_files\figure-html\viz-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+In data modeling there can be instanes where you will want some sort of hyperbolic transformation of your data. In <code>{healthyR.ai}</code> this is easy with the use of the function <code>hai_hyperbolic_…</code><code></code><code></code>
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+<p><a href="./posts/rtip-2022-11-07/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2022-11-07\index_files\figure-html\plt-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+Sometimes in modeling you may want to get a discrete <code>1/0</code> vector of a <code>fourier</code> transform of some input vector. With <code>{healthyR.ai}</code> we can do this easily.
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+Many times in the real world we have a data set which is actually a sample as we typically do not know what the actual population is. This is where <strong>bootstrapping</strong> tends to come into play. It allows us to get a hold on what the possible parameter values are by taking repeated samples of the data that is…
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+<p><a href="./posts/rtip-2022-10-31/index.html"> <p class="card-img-top"><img data-src="posts\rtip-2022-10-31\index_files\figure-html\plt-1.png"  class="thumbnail-image card-img"/></p> </a></p>
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+In this post we will make a function <code>cum_skewness()</code> that will generate a vector output of the cumulative skewness of some given vector. The full function call is simply:
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+In this post we are going to talk about how you can perform <strong>principal component analysis</strong> in <strong>R</strong> with <em>{healthyR.ai}</em> in a <code>tidyverse</code> compliant fashion.
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+Sometimes you may be working with a time series or some process data and you will want to make a control chart. This is simple to do with the <code>{healthyR.ai}</code> package.
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+This is going to be a simple example on how we can make a function in #base #r that will crate a cumulative variance function. From base R we are going to use <code>seq_along()</code>, <code>stats::v…</code><code></code><code></code><em></em>
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+There are two components to time-series clustering with <code>{healthyR.ts}</code>. There is the function that will create the clustering data along with a slew of other information…
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+This is going to serve as a sort of primer for my r packge <code>{healthyR.ai}</code>. The goal of this package is to help with producing uniform <code>machine learning</code>/<code>ai</code> models either from scratch…<code></code>
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+This is going to serve as a sort of primer for the <code>{TidyDensity}</code> package.
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+This is a simple <code>lapply</code> example to start things off.
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+This is the first post in a Quarto blog. Welcome!
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+    <lastmod>2023-11-20T16:38:34.654Z</lastmod>
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