simsem (version 0.2-8)

VirtualDist-class: Distribution Objects

Description

List of all distribution objects. These distribution objects can be used to specify random parameters or specify a marginal distribution of a variable.

Distributions

Here is the list of all distribution objects and the link to their constructors.

• simBetaBeta Distribution
• simBinomBinomial Distribution
• simCauchyCauchy Distribution
• simChisqChi-squared Distribution
• simExpExponential Distribution
• simFF Distribution
• simGammaGamma Distribution
• simGeomGeometric Distribution
• simHyperHypergeometric Distribution
• simLnormLog Normal Distribution
• simLogisLogistic Distribution
• simNbinomNegative Binomial Distribution
• simNormNormal Distribution
• simPoisPoisson Distribution
• simTt Distribution
• simUnifUniform Distribution
• simWeibullWeibull Distribution

Details

These distribution objects can be used to specify random parameters or marginal distribution of variables in Gaussian copula. The random parameter feature is to make data generation parameters different across replications in a simualtion study. The distribution object can be specified as random parameters in simMatrix, symMatrix, simVector, and simResult (in n, pmMCAR, and pmMAR). The distribution object can also be used for specifying marginal distribution of factors, measurement errors, or indicators. See the data distribution object, simDataDist, for how to model marginal distribution of variables, which will be put in setting the data object up, simData.

See Also

List of all distribution objects.

• SimBetaBeta Distribution
• SimBinomBinomial Distribution
• SimCauchyCauchy Distribution
• SimChisqChi-squared Distribution
• SimExpExponential Distribution
• SimFF Distribution
• SimGammaGamma Distribution
• SimGeomGeometric Distribution
• SimHyperHypergeometric Distribution
• SimLnormLog Normal Distribution
• SimLogisLogistic Distribution
• SimNbinomNegative Binomial Distribution
• SimNormNormal Distribution
• SimPoisPoisson Distribution
• SimTt Distribution
• SimUnifUniform Distribution
• SimWeibullWeibull Distribution

Here are the list of possible applications of a distribution object

• simMatrixRandom parameter matrix. A distribution object can be used to create random parameter.
• symMatrixRandom parameter symmetric matrix. A distribution object can be used to create random parameter.
• simVectorRandom parameter vector. A distribution object can be used to create random parameter.
• simResultResult object that saves the result of a simulation study. A distribution object can be used to vary sample size (n), proportion completely missing at random (pmMCAR), or proportion missing at random (pmMAR), which make those factors (e.g., sample size) different across replications.
• simDataDistData distribution object. A distribution object can be used to specify marginal distributions of variables (which can be factors, measurement errors, or indicators).

Examples

showClass("VirtualDist")
u1 <- simUnif(0, 1)
chi3 <- simChisq(3)
summary(chi3)
skew(chi3)
kurtosis(chi3)
plotDist(chi3)
plotDist(chi3, reverse=TRUE)