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Compositional (version 5.5)

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

Run this code
# 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)
# }

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