Weibullmix | R Documentation |
Kiefer-Wolfowitz NPMLE for Weibull Mixtures of scale parameter
Weibullmix(
x,
v = 300,
u = 300,
alpha,
lambda = 1,
event = NULL,
hist = FALSE,
weights = NULL,
...
)
x |
Survival times |
v |
Grid values for mixing distribution |
u |
Grid values for histogram bins, if needed |
alpha |
Shape parameter for Weibull distribution |
lambda |
Scale parameter for Weibull Distribution; must either have length 1, or length
equal to |
event |
censoring indicator, 1 if actual event time, 0 if censored |
hist |
If TRUE aggregate to histogram counts |
weights |
replicate weights for x obervations, should sum to 1 |
... |
optional parameters passed to KWDual to control optimization |
Kiefer Wolfowitz NPMLE density estimation for Weibull scale mixtures. The histogram option is intended for relatively large problems, say n > 1000, where reducing the sample size dimension is desirable. By default the grid for the binning is equally spaced on the support of the data. Parameterization: f(t|alpha, lambda) = alpha * exp(v) * (lambda * t )^(alpha-1) * exp(-(lambda * t)^alpha * exp(v)); shape = alpha; scale = lambda^(-1) * (exp(v))^(-1/alpha) This version purports to handle right censoring.
An object of class density with components
x |
points of evaluation on the domain of the density |
y |
estimated function values at the points x of the mixing density |
logLik |
Log likelihood value at the proposed solution |
dy |
Bayes Rule estimates of mixing parameter |
status |
exit code from the optimizer |
Roger Koenker and Jiaying Gu
Kiefer, J. and J. Wolfowitz Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters Ann. Math. Statist. Volume 27, Number 4 (1956), 887-906.
Koenker, R. and J. Gu, (2017) REBayes: An R Package for Empirical Bayes Mixture Methods, Journal of Statistical Software, 82, 1–26.
Gompertzmix
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