Modification des messages

R/chisquare.test.R

@@ -1,10 +1,12 @@
 # Pearson's Chi-Squared test based on the characteristic function
 # 
 # Author: François Pelletier
+#
+# LGPL 3.0
 ###############################################################################
 
 #' Pearson's Chi-Squared test based on the characteristic function
-#' @param DATA.hist histogram object of the data
+#' @param datahist histogram object of the data
 #' @param FUN Characteristic function (integral) or 
 #' Saddlepoint distribution approximation (saddlepoint)
 #' @param ... FUN arguments
@@ -15,30 +17,26 @@
 #' degree of freedom, hypothesis reject boolean and p.value
 #' @export chisquare.test
 #' @author François Pelletier
-chisquare.test <- function(DATA.hist,FUN,...,alpha=0.05,method="integral")
+chisquare.test <- function(datahist,FUN,...,alpha=0.05,method="integral")
 {
 	# Compute expected values for each histogram breaks using the characteristic function
-	classes <- DATA.hist$breaks
+	classes <- datahist$breaks
+	observed <- datahist$counts
 	if(method=="integral")
 	{
 		expected <- diff(cftocdf(classes,FUN,...)*
-						sum(observed <- DATA.hist$counts))
+						sum(observed))
 	}
 	else if(method=="saddlepoint")
 	{
 		expected <- diff(FUN(classes,...)*
-						sum(observed <- DATA.hist$counts))
+						sum(observed))
 	}
-	
 	# Compute the test statistic using chi-square distribution
-	p.value <- pchisq(chisquare.stat<-sum((observed-expected)^2/expected),
-			df<-length(classes)-2,lower.tail=FALSE)
-	# Print output
-	cat("Chi-Square Test based on CF\n\nTest statistic: ",chisquare.stat,
-			"\nDegree of freedom: ",df,
-			"\nP-value: ",p.value,
-			"\nReject H0 with confidence level ",1-alpha,"?: ",p.value<alpha)
+	chisquare.stat<-sum((observed-expected)^2/expected)
+	df<-length(classes)-2
+	p.value <- pchisq(chisquare.stat,df,lower.tail=FALSE)
 	# Create the return list
-	list(chisquare.stat=chisquare.stat,df=df,reject=p.value<alpha,p.value=p.value)
+	list(chisquare.stat=chisquare.stat,df=df,p.value=p.value)
 }
 

R/md.test.R

@@ -21,17 +21,11 @@ md.test <- function(param,data,t,FUN,empFUN,alpha=0.05)
 	Q <- MASS::ginv(outer(t,t,function(j,k) FUN(j+k,param)-FUN(j,param)*FUN(k,param)))
 	# Vector of differences
 	v <- sqrt(n) * (empFUN(t,data)-FUN(t,param))
-	md.stat <- t(v) %*% Q %*% v
+	md.stat <- Re(as.vector(t(v) %*% Q %*% v))
 	# Compute the test statistic using chi-square distribution
 	p.value <- pchisq(md.stat,df<-length(t))
-	reject <- p.value >= alpha
-	# Print output
-	cat("Minimum distance test based on a transform\n\nTest statistic: ",md.stat,
-			"\nDegree of freedom: ",df,
-			"\nP-value: ",p.value,
-			"\nReject H0 with confidence level ",1-alpha,"?: ",reject)
 	# Create the return list
-	list(md.stat=md.stat,df=df,reject=reject,p.value=p.value)
+	list(md.stat=md.stat,df=df,p.value=p.value)
 }
 
 

man/chisquare.test.Rd

@@ -2,10 +2,10 @@
 \alias{chisquare.test}
 \title{Pearson's Chi-Squared test based on the characteristic function}
 \usage{
-chisquare.test(DATA.hist, FUN, ..., alpha = 0.05, method = "integral")
+chisquare.test(datahist, FUN, ..., alpha = 0.05, method = "integral")
 }
 \arguments{
-  \item{DATA.hist}{histogram object of the data}
+  \item{datahist}{histogram object of the data}
 
   \item{FUN}{Characteristic function (integral) or
   Saddlepoint distribution approximation (saddlepoint)}