Likelihood-Based Statistical Inference with ELiISA Package
University of Turku
ELiISA (Efficient Likelihood-Based Interactive Statistical Analysis) is a package for
calculation of maximum likelihood estimates of parameters, likelihood ratio tests of
hypotheses about parameters, profile likelihood-based confidence intervals for real-valued
parameter functions of interest in various statistical models, such as sampling,
univariate/multivariate linear/nonlinear regression, logistics regression, Poisson
regression, multinomial regression, log-linear, generalized linear models, etc.
ELiISA handles the distributions of statistical models symbolically and provides to the
user access to the cumulative distribution, density, log-likelihood, score, observed
information functions as functions of parameters and observations. It gives access to the
generating functions, moments, cumulants, and expected informations as functions of
parameters. This symbolic handling is necessary for the calculation of certain adjustments
in approximate likelihood-based statistical inference. ELiISA uses a new method for
calculation of profile likelihood-based confidence intervals for general parameter
functions of interest in general parametric statistical models.