Description Usage Arguments Value Examples
View source: R/samplecensored.R
Inverse sampling of censored variables to impute only valid observations, conditional on the respective fit.
1 2 | samplecensored(object, censtype, predictdata, fitdata, censor,
quantiles = c(0.05, 0.25, 0.5, 0.75, 0.95), intervalstart = NULL)
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object |
gamlss object. Fitted model whose parameters are predicted for predictdata. |
censtype |
character. Specifies the type of censoring (right/left/interval/missing). |
predictdata |
dataframe. Predict-data of the missing/censored observations, for which imputations are drawn. |
fitdata |
data.frame. The orignal dataset upon which gamlss was fitted. |
censor |
character. Name of the (damaged) column to be predicted on in predictdata. This is only required if censtype is NOT "missing". |
quantiles |
numeric vector. Containing the quantiles to be evaluated in the conditoned distribution, i.e. conditoned on the parameters and the information contained in the censored value. |
intervalstart |
character. Name of the column of the interval's starting values. By convention, the starting duration in this column is assumed to be the time passed without failure, before entering the interval, in which the exact time of failure is unknown. |
Returns draws and quantiles.
1 2 3 4 5 6 7 8 9 10 11 12 | # Simulating a dataset
ld <- simulateData(n= 300,
param.formula = list(mu = ~exp(x1) + x2 + x3, sigma = ~sin(x2)),
name = 'x1', subset = ~ (x2 < 0.3 & x3 < 0.4), prob = 0.8,
damage =c(0.3, 0.9), family = 'NO',
correlation = NULL)$defected
# Fitting a gamlss model
lmodel <- gamlss(formula = y ~ . -indicator, data=ld)
nl <- length(ld$x1[ld$indicator==1])
lpredict.df <- data.frame(x1 = runif(n = nl), x2 = runif(n = nl), x3 = runif(n = nl), indicator = 1)
samplecensored(lmodel ,censtype = 'left', lpredict.df, ld, censor = "x1")
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