This R package consists of utilities for multivariate inverse Gaussian (MIG) models with mean
-
mig
for the MIG distribution(rmig
for random number generation anddmig
for density) -
tellipt
(rtellipt
for random vector generation anddtellipt
the density) for truncated Student-$t$ or Gaussian distribution over the half space${\boldsymbol{x}: \boldsymbol{\beta}^\top\boldsymbol{x}>\delta}$ for$\delta \geq 0$ . -
fit_mig
to estimate the parameters of the MIG distribution via maximum likelihood (mle
) or the method of moments (mom
).
mig_kdens_bandwidth
to estimate the bandwidth matrix minimizing the asymptotic mean integrated squared error (AMISE) or the leave-one-out likelihood cross validation, minimizing the Kullback--Leibler divergence. Theamise
estimators are estimated by drawing from amig
or truncated Gaussian vector via Monte Carlonormalrule_bandwidth
for the normal rule of Scott for the Gaussian kernelmig_kdens
for the kernel density estimatortellipt_kdens
for the truncated Gaussian kernel density estimator