fun.testpoly: Simulate data from a bivariate normal distribution, and...
In kolassa-dev/TheorStat: Techniques and Concepts from an MS Course in Statistical Theory
fun.testpoly R Documentation
Simulate data from a bivariate normal distribution, and
calculate various measures of association.
Description
Simulate data from a bivariate normal distribution, and
calculate various measures of association.
Usage
fun.testpoly(rho = 0.5, nsamp = 50, nmc = 10000, progress = F)
Arguments
rho
Correlation of marginal normals
nsamp
Number of observations in each sample
nmc
Number of Monte Carlo simulations
progress
Logical indicating whether periodic updates of progress should be made.
Value
list with two components: mat, a matrix with seven columns representing polychoric correlation with 2, 3, and 4 groupings, Pearson correlation, and kappa statistic for 2, 3, and 4 categories., and settings, rho and nsamp.
kolassa-dev/TheorStat documentation built on Dec. 7, 2023, 12:23 a.m.
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| fun.testpoly | R Documentation |
Simulate data from a bivariate normal distribution, and calculate various measures of association.
Description
Simulate data from a bivariate normal distribution, and calculate various measures of association.
Usage
fun.testpoly(rho = 0.5, nsamp = 50, nmc = 10000, progress = F)
Arguments
rho |
Correlation of marginal normals |
nsamp |
Number of observations in each sample |
nmc |
Number of Monte Carlo simulations |
progress |
Logical indicating whether periodic updates of progress should be made. |
Value
list with two components: mat, a matrix with seven columns representing polychoric correlation with 2, 3, and 4 groupings, Pearson correlation, and kappa statistic for 2, 3, and 4 categories., and settings, rho and nsamp.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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