This repo contains data and script for predicting COVID 19 cases for MI across all counties. The prediction model uses Exponential regression. The summary and metrics of the model are as follows
Call:
lm(formula = log(Cases) ~ Day + I(Day^2), data = data[samples,
])
Residuals:
Min 1Q Median 3Q Max
-0.62949 -0.11913 0.07627 0.18488 0.43085
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.421068 0.340882 1.235 0.2480
Day 0.635627 0.091046 6.981 6.46e-05 ***
I(Day^2) -0.010972 0.005013 -2.189 0.0564 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.3344 on 9 degrees of freedom
Multiple R-squared: 0.9815, Adjusted R-squared: 0.9774
F-statistic: 238.4 on 2 and 9 DF, p-value: 1.603e-08
In the below actual vs prediction graph, we can see a good exponential growth curve.