View source: R/user_utilities.R
ic_sample | R Documentation |
Samples response values from an icenReg fit conditional on covariates, but not
censoring intervals. To draw response samples conditional on covariates and
restrained to intervals, see imputeCens
.
ic_sample(fit, newdata = NULL, sampleType = "fullSample", samples = 5)
fit |
icenReg model fit |
newdata |
|
sampleType |
type of samples See details for options |
samples |
Number of samples |
Returns a matrix of samples. Each row of the matrix corresponds with a subject with the
covariates of the corresponding row of newdata
. For each column of the matrix,
the same sampled parameters are used to sample response variables.
If newdata
is left blank, will provide estimates for original data set.
There are several options for how to sample. To get random samples without accounting
for error in the estimated parameters imputeType ='fixedParSample'
takes a
random sample of the response variable, conditional on the response interval,
covariates and estimated parameters at the MLE. Alternatively,
imputeType = 'fullSample'
first takes a random sample of the coefficients,
(assuming asymptotic normality for the ic_par) and then takes a random sample
of the response variable, conditional on the response interval,
covariates, and the random sample of the coefficients.
Clifford Anderson-Bergman
simdata <- simIC_weib(n = 500)
fit <- ic_par(cbind(l, u) ~ x1 + x2,
data = simdata)
newdata = data.frame(x1 = c(0, 1), x2 = c(1,1))
sampleResponses <- ic_sample(fit, newdata = newdata, samples = 100)
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