stpm (version 1.3.2)

simdata_discr: 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)

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.

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. .

Examples

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