#------------------------------------------------------------------
# Program: diagnostics.R
# Objective: graphical functions for diagnostics of linear models
# Author: I.Sanchez
# Creation: 28/07/2016
# Update: 04/09/2020
#------------------------------------------------------------------
#' a function for representing the residuals of a linear model
#' @param fitin is a list containing objects of class lm
#' @return 2 graphs in one page: a graph to check the homoscedasticity of residuals
#' the second to check the normality of the residuals
#' @examples
#' # diagnosticLM() needs a classical linear model list result
#' @export
diagnosticLM<-function(fitin){
par(mfrow=c(2,2))
for (i in 1:length(fitin)){
plot(fitin[[i]],which=1,main=names(fitin)[i])
plot(fitin[[i]],which=2)
}
par(mfrow=c(1,1))
}
#' a function for representing diagnostic graphics for each trait
#' @param datain a dataframe to explore
#' @param xfitted character, name of the column of fitted values
#' @param yresidual character, name of the column of residual values
#' @return a graphic of diagnostic for linear model
#' @importFrom ggplot2 ggplot geom_point geom_hline aes_string
#' @examples
#' # diagnosticResiduals(datain,xfitted,yresidual)
#' @export
#---------------------------------------------------
diagnosticResiduals<-function(datain,xfitted,yresidual){
g<-ggplot(data=datain,ggplot2::aes_string(x=xfitted,y=yresidual)) +
geom_point(size=1) +
geom_hline(yintercept = 2,col="red") +
geom_hline(yintercept = -2,col="red")
print(g)
}
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