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A package for simulating multivariate data with count and continuous variables with a pre-specified correlation matrix and marginal distribution. The count variables are assumed to have Poisson distribution, and continuous variables can take any shape that is allowed by the Fleishman polynomials. This mixed data generation scheme is a combination of the normal to anything principle for the count part, and multivariate continuous data generation mechanism via the Fleishman polynomials.
● Data Source:
CranContrib
● Keywords:
● Alias: PoisNonNor, PoisNonNor-package
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This function sets up formulae that are needed at the subsequent stages.
● Data Source:
CranContrib
● Keywords:
● Alias: fleishman.roots
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This function simulates count and continuous data, where the count part is assumed to follow a multivariate Poisson distribution and the continuous part can take any shape allowed by the Fleishman polynomials. A correlation matrix and marginal features (rate parameter for the count variables, and skewness and kurtosis parameters for the continuous variables must be supplied by users).
● Data Source:
CranContrib
● Keywords:
● Alias: RNG_P_NN
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This function computes the submatrix of the intermediate correlation matrix of the multivariate normal distribution. It is relevant to the count part of the data.
● Data Source:
CranContrib
● Keywords:
● Alias: intercor.PP
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The function checks the validity of pairwise correlations. Additionally, it checks positive definiteness, symmetry and correctness of the dimensions.
● Data Source:
CranContrib
● Keywords:
● Alias: Validate.correlation
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This function computes the submatrix of the intermediate correlation matrix of the multivariate normal distribution. It is relevant to the count-continuous part of the data.
● Data Source:
CranContrib
● Keywords:
● Alias: intercor.NNP
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This function calculates the four coefficients in the Fleishman system given skewness and kurtosis values.
● Data Source:
CranContrib
● Keywords:
● Alias: Param.fleishman
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This function computes the intermediate correlation matrix of the multivariate normal distribution that provides a basis for subsequent tranformations.
● Data Source:
CranContrib
● Keywords:
● Alias: intercor.all
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This function calculates the approximate lower and upper bounds for all continuous-count pairs by the method in Demirtas and Hedeker (2011).
● Data Source:
CranContrib
● Keywords:
● Alias: bounds.corr.GSC.NNP
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This function calculates the approximate lower and upper bounds for all count pairs by the method in Demirtas and Hedeker (2011).
● Data Source:
CranContrib
● Keywords:
● Alias: bounds.corr.GSC.PP
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