Compositional (version 5.4)

Hotelling's multivariate version of the 1 sample t-test for Euclidean data: Hotelling's multivariate version of the 1 sample t-test for Euclidean data

Description

Hotelling's test for testing one Euclidean population mean vector.

Usage

hotel1T2(x, M, a = 0.05, R = 999, graph = FALSE)

Arguments

x

A matrix containing Euclidean data.

a

The significance level, set to 0.05 by default.

M

The hypothesized mean vector.

R

If R is 1 no bootstrap calibration is performed and the classical p-value via the F distribution is returned. If R is greater than 1, the bootstrap p-value is returned.

graph

A boolean variable which is taken into consideration only when bootstrap calibration is performed. IF TRUE the histogram of the bootstrap test statistic values is plotted.

Value

A list including:

m

The sample mean vector.

info

The test statistic, the p-value, the critical value and the degrees of freedom of the F distribution (numerator and denominator). This is given if no bootstrap calibration is employed.

pvalue

The bootstrap p-value is bootstrap is employed.

runtime

The runtime of the bootstrap calibration.

Details

Multivariate hypothesis test for a one sample mean vector. This is the multivariate analogue of the one sample t-test. The p-value can be calculated either asymptotically or via bootstrap.

References

K.V. Mardia, J.T. Kent and J.M. Bibby (1979). Multivariate analysis.

See Also

eel.test1, el.test1, james, hotel2T2, maov, el.test2, comp.test

Examples

# NOT RUN {
x <- Rfast::rmvnorm(100, numeric(10), diag( rexp(10,0.5) ) )
hotel1T2(x, numeric(10), R = 1)
hotel1T2(x, numeric(10), R = 999, graph = TRUE)
# }