MVcis: Calculate Hotelling's T2 Confidence Intervals

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/MVcis.R

Description

Calculate joint confidence intervals (Hotelling's T2 Intervals).

Usage

1
MVcis(data, segments = 51, level = .95, Vars2Plot = c(1, 2), include.zero = F)

Arguments

data

a multivariable dataset to compare to means

segments

number of line-segments used to draw ellipse.

level

draw elliptical contours at these (normal) probability or confidence levels.

Vars2Plot

variables to plot

include.zero

add the zero axis to the graph output

Details

This function calculates the Hotelling's T2 Intervals for a mean vector.

Assumption:

Population is a random sample from a multivariate population.

If the confidence ellipse does not cover c(0, 0), we reject the NULL that the joint confidence region is equal to zero (at the stated alpha level).

Value

This function returns the Hotelling's T2 confidence intervals for the p-variates and its corresponding confidence ellipse at the stated confidence level.

Author(s)

Nelson Lee Afanador ([email protected])

References

Johnson, R.A., Wichern, D.W. (2002) Applied Multivariate Statistical Analysis. Prentice Hall.

See Also

MVComp

Examples

1
2
data(College)
MVcis(College, Vars2Plot = c(1, 2), include.zero = TRUE)

Example output

             [,1]      [,2]
Social  502.99940 550.17302
Verbal   51.21484  58.16447
Science  23.63855  26.61432

mvdalab documentation built on Nov. 17, 2017, 6 a.m.