make.data.set: Data matrix for dynamic landmark prediction of mixture data
In tpgarcia/stride: STRIDE: Robust powerful mixture models

Create data set based on user input.

make.data.set(
  n,
  m,
  p,
  qvs,
  q,
  x,
  delta,
  ww,
  zz,
  know.true.groups,
  true.group.identifier
)

`n`	sample size, must be at least 1.
`m`	number of different mixture proportions, must be at least 2.
`p`	number of populations, must be at least 2.
`qvs`	a numeric matrix of size `p` by `m` containing all possible mixture proportions (i.e., the probability of belonging to each population k, k=1,...,p.).
`q`	a numeric matrix of size `p` by `n` containing the mixture proportions for each person in the sample.
`x`	a numeric vector of length `n` containing the observed event times for each person in the sample.
`delta`	a numeric vector of length `n` that denotes censoring (1 denotes event is observed, 0 denotes event is censored).
`ww`	a numeric vector of length `n` containing the values of the continuous covariate for each person in the sample. Can be NULL.
`zz`	a numeric vector of length `n` containing the values of the discrete covariate for each person in the sample. Can be NULL.
`know.true.groups`	logical indicator. If TRUE, then we know the population identifier for each person in the sample. This option is only used for simulation studies. Default is FALSE.
`true.group.identifier`	numeric vector of length `n` denoting the population identifier for each person in the sample. Default is NULL.

a matrix of the concatenated data. The columns are "x", "delta", "q1" to "qp" (correspond to the mixture proportions), "w" (for ww if non-NULL), "z" (for zz if non-NULL), "uset" (for "u-set" meaning the uth mixture proportion group), and "group" (for the true population group as defined by true.group.identifier). If know.true.groups is FALSE, then the column "group" is a vector of 0's.

tpgarcia/stride documentation built on March 18, 2021, 3:42 p.m.