NPmix | R Documentation |
Interior point solution of Kiefer-Wolfowitz NPMLE for mixture of Normal/Poissons
NPmix(x, m, v = 50, u = 50, weights = NULL, ...)
x |
observed response for Gaussian observations |
m |
Number of trials for Poisson observations |
v |
Grid Values for the Gaussian means mixing distribution defaults to equal spacing of length v on [min(x) + eps, max(x) - eps], if v is scalar. |
u |
Grid Values for the Poisson rate mixing distribution defaults to equal spacing of length u on [min(m) + eps, max(m) - eps], if u is scalar. |
weights |
replicate weights for x obervations, should sum to 1 |
... |
Other arguments to be passed to KWDual to control optimization |
The joint distribution of the means and the number of trials determining sample standard
deviations is estimated. The grid specification for means is as for GLmix
whereas the grid for the Poisson rate parameters by default depends on the support of the
observed trials. There is no predict method as yet. See demo(NPmix1)
.
An object of class density with components:
v |
grid points of evaluation of the success probabilities |
u |
grid points of evaluation of the Poisson rate for number of trials |
y |
function values of the mixing density at (v,u) |
g |
estimates of the mixture density at the distinct data values |
logLik |
Log Likelihood value at the estimate |
status |
exit code from the optimizer |
R. Koenker and J. Gu
Kiefer, J. and J. Wolfowitz Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters Ann. Math. Statist. 27, (1956), 887-906.
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