GenerateMultivariate: Generate dataset with multiple individual identity traits

In IDmeasurer: Assessment of Individual Identity in Animal Signals

Description

This functions generates a dataset with desired parameters (number of individuals and number of observations per individual, number of variables and covariance between variables, individuality). Unlike for the function GenerateUnivariate, trait means are not customizable and are always set to 0.

Usage

GenerateMultivariate(nindivs, nobs, nvars, covar, individuality)

Arguments

nindivs	Indicates how many individuals should be in dataset
nobs	Indicates how many observations per individual should be in dataset
nvars	Indicates how many trait variables should be in dataset.
covar	Indicates covariance between variables in dataset. covar=0 for uncorrelated variables; covar=1 for fully correlated variables
individuality	Indicates the ratio of between to within individual variation in each trait variable.

Value

Data frame with the identity codes in the first column and trait variables in subsequent columns. Number of rows and columns depends on the parameters used to generate dataset.

See Also

Other Operations with datasets: GenerateUnivariate

Examples

id1 <- GenerateMultivariate(nindivs=10, nobs=10, nvars=2, covar=0, individuality=1)

IDmeasurer documentation built on May 9, 2019, 5:02 p.m.