Shewhart plots in R

Installation

To install the package from Github you can use the install_github command from the devtools package:

devtools::install_github("castlaboratory/Shewhart")

You could also download the repository and install via local package installation on R.

install.packages("Shewhart.zip", repos = NULL)

Usage

Data

cvd_recife <- read_rds(system.file("extdata", package = "Shewhart", file = "recife_2020_covid19.rds"))

cvd_recife %>% glimpse()

## Rows: 279
## Columns: 2
## $ data        <date> 2020-03-28, 2020-03-29, 2020-03-30, 2020-03-31, 2020-04-0…
## $ obitosNovos <int> 4, 0, 0, 0, 1, 1, 0, 4, 4, 2, 2, 4, 5, 5, 2, 3, 9, 3, 13, …

GGPLOT

shewhart(data = cvd_recife, 
         index_col = data,
         values_col = obitosNovos, 
         locale = "en_US")

shewhart(data = cvd_recife, 
         index_col = data,
         values_col = obitosNovos, 
         model = "loglog",
         locale = "en_US")

PLOTLY

shewhart(data = cvd_recife, 
         index_col = data,
         values_col = obitosNovos, 
         locale = "en_US", 
         model = "log",
         type = "plotly")

Autodetect phases

You can use the 7-point rule with the command shewhart_7points

phase_dates <- shewhart_7points(data = cvd_recife, 
                                index_col = data, 
                                values_col = obitosNovos)
print(phase_dates)

##  [1] "2020-04-07" "2020-05-06" "2020-06-04" "2020-06-15" "2020-06-22"
##  [6] "2020-07-04" "2020-07-15" "2020-08-06" "2020-08-29" "2020-12-08"
## [11] "2020-12-21" "2020-12-28"

You can get de model using these dates with the command shewhart_model

shwt_model <- shewhart_model(data = cvd_recife,
                             index_col = data,
                             values_col = obitosNovos, 
                             phase_changes = phase_dates)

shwt_model %>% head()

## # A tibble: 6 × 18
##   phase data       obitosNovos change model  flag     N fit    tidied   fitted
##   <int> <date>           <int> <lgl>  <chr> <int> <int> <list> <list>    <dbl>
## 1     0 2020-03-28           4 FALSE  log       0     1 <lm>   <tibble>  0.330
## 2     0 2020-03-29           0 FALSE  log       0     2 <lm>   <tibble>  0.419
## 3     0 2020-03-30           0 FALSE  log       0     3 <lm>   <tibble>  0.508
## 4     0 2020-03-31           0 FALSE  log       0     4 <lm>   <tibble>  0.598
## 5     0 2020-04-01           1 FALSE  log       0     5 <lm>   <tibble>  0.687
## 6     0 2020-04-02           1 FALSE  log       0     6 <lm>   <tibble>  0.776
## # … with 8 more variables: residuals <dbl>, CONL_1 <dbl>, UCL <dbl>, LCL <dbl>,
## #   CL <dbl>, UL_EXP <dbl>, LL_EXP <dbl>, phase_string <chr>

If you already have the dates or the model you can use it to make the plot

shewhart(data = cvd_recife, 
         index_col = data,
         values_col = obitosNovos, 
         model = "loglog",
         locale = "en_US",
         phase_changes = phase_dates)

shewhart(data = shwt_model, 
         index_col = data,
         values_col = obitosNovos, 
         model = "loglog",
         locale = "en_US")

Depedencies

this package depends of:

• lubridate (>= 1.8.0),
• tidyverse (>= 1.3.0),
• tibbletime (>= 0.1.6),
• tidymodels (>= 1.0.0),
• pals (>= 1.7),
• scales (>= 1.2.1),
• plotly (>= 4.1)

Stay Tuned

Please visit the castlab.org for latest updates and news.