simdata_discr: Multi-dimension simulation function

In izhbannikov/spm: Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes

Multi-dimension simulation function

Description

Multi-dimension simulation function

Usage

simdata_discr(
  N = 100,
  a = -0.05,
  f1 = 80,
  Q = 2e-08,
  f = 80,
  b = 5,
  mu0 = 1e-05,
  theta = 0.08,
  ystart = 80,
  tstart = 30,
  tend = 105,
  dt = 1,
  nobs = NULL,
  format = "long"
)

Arguments

N	Number of individuals
a	A k by k matrix, which characterize the rate of the adaptive response.
f1	A particular state, which is a deviation from the normal (or optimal). This is a vector with length of k.
Q	A matrix k by k, which is a non-negative-definite symmetric matrix.
f	A vector-function (with length k) of the normal (or optimal) state.
b	A diffusion coefficient, k by k matrix.
mu0	mortality at start period of time.
theta	A displacement coefficient of the Gompertz function.
ystart	A vector with length equal to number of dimensions used, defines starting values of covariates. Default ystart = 80.
tstart	Starting time (age). Can be a number (30 by default) or a vector of two numbers: c(a, b) - in this case, starting value of time is simulated via uniform(a,b) distribution.
tend	A number, defines final time (105 by default).
dt	A time step (1 by default).
nobs	A number, defines a number of observations (lines) for an individual, NULL by default.
format	Data format: "long" (default), "short".

Value

A table with simulated data.

References

Akushevich I., Kulminski A. and Manton K. (2005), Life tables with covariates: Dynamic model for Nonlinear Analysis of Longitudinal Data. Mathematical Population Studies, 12(2), pp.: 51-80. <DOI:10.1080/08898480590932296>.

Examples

library(stpm)
data <- simdata_discr(N=100)
head(data)

izhbannikov/spm documentation built on Sept. 10, 2022, 12:15 p.m.