| par_logn_mix_known {LNPar} | R Documentation |
Estimate the parameters of a lognormal-Pareto density, assuming a known threshold
Description
This function estimates the parameters of a Pareto and a lognormal density, assuming a known threshold.
Usage
par_logn_mix_known(y, prior1, th, alpha, mu, sigma)
Arguments
y |
non-negative numerical vector: random sample from the mixture. |
prior1 |
scalar (0<prior1<1): starting value of the prior probability. |
th |
positive scalar: threshold. |
alpha |
non-negative scalar: starting value of the Pareto shape parameter. |
mu |
scalar: starting value of the lognormal parameter mu. |
sigma |
positive scalar: starting value of the lognormal parameter sigma. |
Value
A list with the following elements:
xmin: estimated threshold.
prior: estimated mixing weight.
post: matrix of posterior probabilities.
alpha: estimated Pareto shape parameter.
mu: estimated expectation of the lognormal distribution on the lognormal scale.
sigma: estimated standard deviation of the lognormal distribution on the lognormal scale.
loglik: maximized log-likelihood.
nit: number of iterations.
Examples
mixFit <- par_logn_mix_known(TN2016, .5, 4700, 3, 7, 1.2)