fmrs.gendata method

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Description

Generates a data set from Finite Mixture of AFT regression models or Finite Mixture of Regression models under the specified setting.

Usage

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fmrs.gendata(nObs, nComp, nCov, coeff, dispersion, mixProp, rho, umax, ...)

## S4 method for signature 'ANY'
fmrs.gendata(nObs, nComp, nCov, coeff, dispersion, mixProp, rho,
  umax, disFamily = "lnorm")

Arguments

nObs

A numeric value represents sample size

nComp

A numeric value represents the order mixture in FMRs model

nCov

A numeric value represents the number of covariates in design matrix

coeff

A vector of all regression coefficients including intercepts. It must be a vector of length nComp *(nCov+1).

dispersion

A vector of positive values for dispersion parameters of sub-distributions in FMRs models

mixProp

A vector of mixing proportions which their sum must be one

rho

A numeric value in [-1, 1] which represents the correlation between covariates of design matrix

umax

A numeric value represents the upper bound in Uniform distribution for censoring

...

Other possible options

disFamily

A sub-distribution family. The options are "norm" for FMR models, "lnorm" for mixture of AFT regression models with Log-Normal sub-distributions,"weibull" for mixture of AFT regression models with Weibull sub-distributions

Value

A list including reponse, covariates and cenroing variables

Author(s)

Farhad Shokoohi <shokoohi@icloud.com>

See Also

Other lnorm..norm..weibull: fmrs.mle, fmrs.tunsel, fmrs.varsel

Examples

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set.seed(1980)
nComp = 2
nCov = 10
nObs = 500
REP = 500
dispersion = c(1, 1)
mixProp = c(0.4, 0.6)
rho = 0.5
coeff1 = c( 2,  2, -1, -2, 1, 2, 0, 0,  0, 0,  0)
coeff2 = c(-1, -1,  1,  2, 0, 0, 0, 0, -1, 2, -2)
umax = 40

dat <- fmrs.gendata(nObs = nObs, nComp = nComp, nCov = nCov,
                     coeff = c(coeff1, coeff2), dispersion = dispersion,
                     mixProp =mixProp, rho = rho, umax = umax,
                     disFamily = "lnorm")