Simulation function for continuous trait with time-dependant coefficients.
simdata_time_dep(
N = 10,
f = list(at = "-0.05", f1t = "80", Qt = "2e-8", ft = "80", bt = "5", mu0t = "1e-3"),
step = 1,
tstart = 30,
tend = 105,
ystart = 80,
sd0 = 1,
nobs = NULL,
format = "short"
)
A table with simulated data.
Number of individuals.
a list of formulas that define age (time) - dependency. Default: list(at="a", f1t="f1", Qt="Q*exp(theta*t)", ft="f", bt="b", mu0t="mu0*exp(theta*t)")
An interval between two observations, a random uniformally-distributed value is then added to this step.
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.
A number, defines final time (105 by default).
A starting value of covariates.
A standard deviation for modelling the next covariate value, sd0 = 1 by default.
A number of observations (lines) for individual observations.
Data format: "short" (default), "long".
Yashin, A. et al (2007), Health decline, aging and mortality: how are they related? Biogerontology, 8(3), 291-302.<DOI:10.1007/s10522-006-9073-3>.
library(stpm)
dat <- simdata_time_dep(N=100)
head(dat)
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