error_vars: Generate Variables for Error Loop
In SimMultiCorrData: Simulation of Correlated Data with Multiple Variable Types

Description Usage Arguments Value References See Also

This function simulates the continuous, ordinal (r >= 2 categories), Poisson, or Negative Binomial variables used in error_loop. It is called in each iteration, regenerates all variables, and calculates the resulting correlation matrix. This function would not ordinarily be called directly by the user.

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error_vars(marginal, support, method, means, vars, constants, lam, size, prob,
  mu, Sigma, rho_calc, q, r, k_cat, k_cont, k_pois, k_nb, Y_cat, Y, Yb, Y_pois,
  Y_nb, n, seed)

`marginal`	a list of length equal `k_cat`; the i-th element is a vector of the cumulative probabilities defining the marginal distribution of the i-th variable; if the variable can take r values, the vector will contain r - 1 probabilities (the r-th is assumed to be 1)
`support`	a list of length equal `k_cat`; the i-th element is a vector of containing the r ordered support values; if not provided, the default is for the i-th element to be the vector 1, ..., r
`method`	the method used to generate the continuous variables. "Fleishman" uses a third-order polynomial transformation and "Polynomial" uses Headrick's fifth-order transformation.
`means`	a vector of means for the continuous variables
`vars`	a vector of variances
`constants`	a matrix with `k_cont` rows, each a vector of constants c0, c1, c2, c3 (if `method` = "Fleishman") or c0, c1, c2, c3, c4, c5 (if `method` = "Polynomial"), like that returned by `find_constants`
`lam`	a vector of lambda (> 0) constants for the Poisson variables (see `Poisson`)
`size`	a vector of size parameters for the Negative Binomial variables (see `NegBinomial`)
`prob`	a vector of success probability parameters
`mu`	a vector of mean parameters (*Note: either `prob` or `mu` should be supplied for all Negative Binomial variables, not a mixture)
`Sigma`	the 2 x 2 intermediate correlation matrix generated by `error_loop`
`rho_calc`	the 2 x 2 final correlation matrix calculated in `error_loop`
`q`	the row index of the 1st variable
`r`	the column index of the 2nd variable
`k_cat`	the number of ordinal (r >= 2 categories) variables
`k_cont`	the number of continuous variables
`k_pois`	the number of Poisson variables
`k_nb`	the number of Negative Binomial variables
`Y_cat`	the ordinal variables generated from `error_loop`
`Y`	the continuous (mean 0, variance 1) variables
`Yb`	the continuous variables with desired mean and variance
`Y_pois`	the Poisson variables
`Y_nb`	the Negative Binomial variables
`n`	the sample size
`seed`	the seed value for random number generation