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where n is the sample size, nComp is the order of FMRs model, nCov is the number of regression covariates, coeff, dispersion and mixProp are the parameters of regression models, i.e. regression coefficients, dispersion (standard deviation) of the errors (sub-distributions) and mixing proportions, respectively, and rho is the used in the variance-covariance matrix for simulating the design matrix x, and umax is the upper bound for Uniform distribution for generating censoring times.
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Depending on the choice of disFamily, the function fmrs.gendata generates a simulated data from FMRs models. For instance, if we choose disFamily = "norm", the function ignores the censoring parameter umax and generates a data set from an FMR model with Normal sub-distributions. However, if we choose disFamily = "lnorm" or disFamily = "weibull", the function generates data under a finite mixture of AFT regression model with Log-Normal or Weibull sub-distributions. 2351a5e196
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