fmrs.gendata {fmrs} | R Documentation |
Generates a data set from Finite Mixture of AFT regression models or Finite Mixture of Regression models under the specified setting.
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" )
nObs |
A numeric value represents sample size |
nComp |
A numeric value represents the order mixture in |
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
|
dispersion |
A vector of positive values for dispersion parameters of
sub-distributions in |
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 |
A list including reponse, covariates and cenroing variables
Farhad Shokoohi <shokoohi@icloud.com>
Other lnorm, norm, weibull:
fmrs.mle()
,
fmrs.tunsel()
,
fmrs.varsel()
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')