m.test | R Documentation |
Automatic average/median/variance comparison function.
m.test(
data,
cat,
alpha = 0.05,
verbose = TRUE,
return = TRUE,
paired = FALSE,
control = c(),
maxcat = 50,
plot = TRUE,
silent = TRUE,
boot = TRUE,
iter = 500,
conf = 0.95,
code = FALSE,
debug = FALSE
)
data |
numerical vector |
cat |
category vector |
alpha |
p-value threshold value for all the tests. |
verbose |
to display the full reasoning of the analysis. |
return |
allows to return the results of pairwise analysis (p-values and groups). |
paired |
(under development) to allow the analysis of matched data. |
control |
name of the category that will eventually be used as a control. |
maxcat |
maximum number of categories allowed. When this number is high, some tests may return an error message. |
plot |
to display the distribution of the data. |
silent |
for displaying or not warnings. |
boot |
to activate the boostrap on 'mean' and 'median'. |
iter |
number f iterations (boot==TRUE). |
conf |
confidence level of bootstrap. |
code |
allows to display the simplified R source code to be able to do the same R study step by step. |
debug |
when m.test return error. |
m.test() runs a decision tree to choose the most appropriate test series for sample comparison.
She chooses the tests, justifies her choices.
It can output groups of means or a comparison to a control.
Finally, it will measure the robustness of the results by bootstrap.
data(iris)
m.test(iris[,1],iris[,5],verbose=TRUE, return=TRUE)
m.test(iris[1:100,1],iris[1:100,5],verbose=TRUE, return=TRUE)
m.test(iris[,2],iris[,5],verbose=TRUE, return=TRUE)
m.test(iris[,3],iris[,5],verbose=TRUE, return=TRUE)
m.test(iris[,4],iris[,5],verbose=TRUE, plot=FALSE, return=FALSE, boot=FALSE)
m.test(iris[,1],iris[,5],verbose=TRUE, return=TRUE,control="setosa")
m.test(iris[,2],iris[,5],verbose=TRUE, return=TRUE,control="virginica")
m.test(iris[,3],iris[,5],verbose=TRUE, return=TRUE,control="setosa")
m.test(iris[,4],iris[,5],verbose=TRUE, return=TRUE,control="setosa")
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