examineNormality

X<-df[,1:12]
exam.norm<-function(X,univariate=T,univariate.test=F,bivariate=F,multivariate=T){
 if(univariate==T){
 if(ncol(X)==1){par(mfrow=c(1,1))}
 if(ncol(X)>1&ncol(X)<4){par(mfrow=c(1,ncol(X)))}
 if(ncol(X)>3){par(mfrow=c(ceiling(ncol(X)/3),3))}
 for(i in 1:(ncol(X))){
 qqnorm(X[i],ylab=colnames(X)[i], xlab=paste("normal","quantiles"),main="QQNORM")}}
 if(sum(univariate,bivariate,multivariate)>1){windows()}
 if(bivariate==T){
 panel.hist<- function(x, ...){
 usr <- par("usr"); on.exit(par(usr))
 par(usr = c(usr[1:2], 0, 1.5) )
 h <- hist(x,plot=F)
 breaks <- h$breaks; nB <- length(breaks)
 y <- h$counts; y <- y/max(y)
 rect(breaks[-nB], 0, breaks[-1], y, col="bisque4", ...)}
 pairs(X,diag.panel=panel.hist)}
 if(sum(univariate,bivariate,multivariate)==3){windows()}
 if(multivariate==T){
 mu<-colMeans(X)
 sig<-cov(X)
 stopifnot(mahalanobis(X,0,diag(ncol(X)))==rowSums(X*X))
 par(mfrow=c(2,1))
 D2<-mahalanobis(X,mu,sig)
 n=dim(X)[1];p=dim(X)[2]
 plot(density(D2,bw=.5),main=paste("Mahalanobis Distances (N=",as.character(n),"& p=",as.character(p),")"))
 qqnorm(qchisq(ppoints(n),df=p),D2,main="Q-Q Plot of Mahalanobis D Squared vs.Quantiles of Chi Squared")
 abline(0,1,col='gray')
 }
if(univariate==F&multivariate==F&bivariate==F){print("User must specify at least
one method of examining for normality")}
 if(univariate.test==T){
 results<-vector("list",ncol(X))
 for(i in 1:(ncol(X))){
 results[[i]]<-shapiro.test(X[,i])}
 names(results)<-colnames(X)
 print(results)
 }
}


exam.norm(X,univariate=T,univariate.test=F,bivariate=T,multivariate=T)