meanTest.two {MNormTest} | R Documentation |
Test whether the mean vectors of two multivariate normal populations are equal when the covariance matrices are equal or unequal. The null hypothesis is that "H0: mu1 = mu2".
meanTest.two(
data1,
data2,
alpha = 0.05,
equal = TRUE,
method = c("None", "Coupled", "Transformed"),
verbose = TRUE
)
data1 |
A matrix or data frame of group 1. |
data2 |
A matrix or data frame of group 2. |
alpha |
The significance level. Default is 0.05. |
equal |
A boolean value. Default is TRUE. If TRUE, the covariance matrix is equal. If FALSE, the covariance matrix is not equal. |
method |
A string value. Default is "None". When equal is FALSE, you must choose a method in "Coupled" or "Transformed". Choose "Coupled" when the sample size of two groups is equal. Choose "Transformed" when the sample size of two groups is not equal. |
verbose |
A boolean value. Default is TRUE. If TRUE, the null hypothesis will be displayed. If FALSE, the test will be carried out silently. |
An object of class "testResult", which is a list with the following elements: Return when the param equal is TRUE.
Conclusion |
The conclusion of the test. |
Stat |
A data frame containing the statistics, p value and critical value. |
SampMean1 |
The sample mean of group 1. |
SampMean2 |
The sample mean of group 2. |
SampA1 |
The sample deviation of group 1. |
SampA2 |
The sample deviation of group 2. |
MixSampA |
The mixed sample deviation. |
Df |
The degree of freedom. |
Return when the param equal is FALSE and method is "Coupled".
Conclusion |
The conclusion of the test. |
Stat |
A data frame containing the statistics, p value and critical value. |
SampMeanC |
The sample mean of coupled data. |
SampAC |
The sample deviation of coupled data. |
Df |
The degree of freedom. |
dataC |
The coupled data. |
Return when the param equal is FALSE and method is "Transformed".
Conclusion |
The conclusion of the test. |
Stat |
A data frame containing the statistics, p value and critical value. |
SampMeanT |
The sample mean of transformed data. |
SampAT |
The sample deviation of transformed data. |
Df |
The degree of freedom. |
dataT |
The transformed data. Return when the param equal is FALSE and method is "Transformed". |
Xifeng Zhang
Huixuan, Gao. Applied Multivariate Statistical Analysis. Peking University Press, 2005: pp.76-80.
data(iris)
X <- iris[1:50, 1:4]
Y <- iris[51:100, 1:4]
# carry out the test
test1 <- meanTest.two(X, Y)
test2 <- meanTest.two(X, Y, verbose = TRUE)
test3 <- meanTest.two(X, Y, equal = FALSE, method = "Coupled")
test4 <- meanTest.two(X, Y, equal = FALSE, method = "Transformed")
# get the elements
test1$Stat
test1$SampMean1
test3$SampMeanC
test4$dataT