View source: R/mean2_1931Hotelling.R

mean2.1931Hotelling | R Documentation |

Given two multivariate data *X* and *Y* of same dimension, it tests

*H_0 : μ_x = μ_y\quad vs\quad H_1 : μ_x \neq μ_y*

using the procedure by Hotelling (1931).

mean2.1931Hotelling(X, Y, paired = FALSE, var.equal = TRUE)

`X` |
an |

`Y` |
an |

`paired` |
a logical; whether you want a paired Hotelling's test. |

`var.equal` |
a logical; whether to treat the two covariances as being equal. |

a (list) object of `S3`

class `htest`

containing:

- statistic
a test statistic.

- p.value
*p*-value under*H_0*.- alternative
alternative hypothesis.

- method
name of the test.

- data.name
name(s) of provided sample data.

hotelling_generalization_1931SHT

## CRAN-purpose small example smallX = matrix(rnorm(10*3),ncol=3) smallY = matrix(rnorm(10*3),ncol=3) mean2.1931Hotelling(smallX, smallY) # run the test ## generate two samples from standard normal distributions. X = matrix(rnorm(50*5), ncol=5) Y = matrix(rnorm(77*5), ncol=5) ## run single test print(mean2.1931Hotelling(X,Y)) ## empirical Type 1 error niter = 1000 counter = rep(0,niter) # record p-values for (i in 1:niter){ X = matrix(rnorm(50*5), ncol=5) Y = matrix(rnorm(77*5), ncol=5) counter[i] = ifelse(mean2.1931Hotelling(X,Y)$p.value < 0.05, 1, 0) } ## print the result cat(paste("\n* Example for 'mean2.1931Hotelling'\n","*\n", "* number of rejections : ", sum(counter),"\n", "* total number of trials : ", niter,"\n", "* empirical Type 1 error : ",round(sum(counter/niter),5),"\n",sep=""))

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