Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
R
 
 
man
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Violets are BLUE. OLS is too.

violets is a package for R which re-estimates fancy statistical models using simple OLS.

Original idea by @abhworthington. Hex logo by @researchremora. Thanks!

Install and load:

# install from github
library(remotes)
install_github('vincentarelbundock/violets')
# load
library(violets)

Your Poisson model of horse kicks to the head could be BLUE:

url <- 'https://vincentarelbundock.github.io/Rdatasets/csv/pscl/prussian.csv'
dat <- read.csv(url, stringsAsFactors = FALSE)

mod <- glm(y ~ corp + year, data = dat, family = 'poisson')
violets(mod)
## Violets are BLUE. OLS is too.

## 
## Call:
## stats::lm(formula = f, data = mf)
## 
## Coefficients:
## (Intercept)        corpI       corpII      corpIII       corpIV       corpIX  
##  -3.073e-01   -1.874e-15   -2.000e-01   -2.000e-01   -4.000e-01   -1.500e-01  
##       corpV       corpVI      corpVII     corpVIII        corpX       corpXI  
##  -2.500e-01    5.000e-02   -2.000e-01   -4.500e-01   -5.000e-02    4.500e-01  
##     corpXIV       corpXV         year  
##   4.000e-01   -4.000e-01    1.310e-02

Your probit model of deaths aboard the titanic could be BLUE:

url <- 'http://vincentarelbundock.github.io/Rdatasets/csv/Stat2Data/Titanic.csv'
dat <- read.csv(url, stringsAsFactors = FALSE)

mod <- glm(Survived ~ Sex + Age + PClass, data = dat, family = binomial(link = 'probit'))
violets(mod)
## Violets are BLUE. OLS is too.

## 
## Call:
## stats::lm(formula = f, data = mf)
## 
## Coefficients:
## (Intercept)      Sexmale          Age    PClass2nd    PClass3rd  
##    1.130523    -0.501326    -0.006005    -0.207434    -0.393344

Your ordered logit model of ??? could be BLUE:

library(MASS)
url <- 'https://vincentarelbundock.github.io/Rdatasets/csv/geepack/koch.csv'
dat <- read.csv(url, stringsAsFactors = FALSE)

dat$y <- as.factor(dat$y)
mod <- polr(y ~ day + trt, data = dat)

violets(mod)
## Violets are BLUE. OLS is too.

## 
## Call:
## stats::lm(formula = f, data = mf)
## 
## Coefficients:
## (Intercept)          day          trt  
##     2.70219     -0.06464     -0.36806

About

Violets are BLUE. OLS is too. (R package)

Resources

License

Releases

No releases published

Packages

No packages published

Languages