qqmat: Q-Q plot to assess normality of data

In zarquon42b/Morpho: Calculations and Visualisations Related to Geometric Morphometrics

Q-Q plot to assess normality of data

Description

qqmat plots Mahalanobisdistances of a given sample against those expected from a Gaussian distribution

Usage

qqmat(x, output = FALSE, square = FALSE)

Arguments

x	sample data: matrix or vector
output	logical: if TRUE results are returned
square	plot in a square window - outliers might be cut off.

Value

if output=TRUE, the following values are returned

x	distances from an expected Gaussian distribution
y	observed distances - sorted
d	observed distances - unsorted

Author(s)

Stefan Schlager

See Also

qqplot

Examples

require(MASS)
### create normally distributed data
data <- mvrnorm(100,mu=rep(0,5),Sigma = diag(5:1))
qqmat(data)

###create non normally distributed data
data1 <- rchisq(100,df=3)
qqmat(data1,square=FALSE)

zarquon42b/Morpho documentation built on Jan. 28, 2024, 2:11 p.m.