- Fixed installation error when using clang compiler
Prerequisite for Package Usage:
- Since RcppArmadillo is used, the R version should be at least 3.3.0 (listed under Depends in DESCRIPTION file)
New Features:
- Vignettes for non-parametric probability estimation, parameter estimation using Median-Rank Regression and Maximum-Likelihood and mixture model estimation are provided.
- Argument y in functions plot_prob_mix() and plot_mod_mix() is deprecated and not used anymore.
- Argument reg_output in functions plot_prob_mix() and plot_mod_mix() is deprecated; use mix_output instead.
- Function plot_mod_mix() was revised and updated in the way that the obtained results of the function mixmod_em() can be visualized.
- Function plot_prob_mix() was revised and updated in the way that the obtained results of the function mixmod_em() can be visualized.
- Implementation of EM-Algorithm using Newton-Raphson. The algorithm is written in c++ (mixture_em_cpp()) and is called in mixmod_em().
- New method for the computation of Fisher’s Confidence Bounds regarding probabilities is used. These method is called “z-Procedure” and is more appropriate to manage the bend-back behaviour. Therefore an adjustment of functions delta_method() and confint_fisher() was made.
- Implementation of log-location-scale models with threshold parameter like three-parametric weibull (“weibull3”), three-parametric lognormal (“lognormal3”) and three-parametric loglogistic (“loglogistic3”).
- Implementation of location-scale models like smallest extreme value (“sev”), normal (“normal”) and logistic (“logistic”).
- Implementation of Log-Likelihood Profiling for three-parametric models in function loglik_profiling(). In general this function is used inside ml_estimation() for the purpose of estimating threshold parameter of three-parametric models.
- Implementation of R-Squared Profiling for three-parametric models in function r_squared_profiling(). In general this function is used inside rank_regression() for the purpose of estimating threshold parameter of three-parametric models.
- Implementation of Log-Likelihood Function for all implemented models in function loglik_function(). In general this function is used inside ml_estimation() for the purpose of estimating the variance-covariance matrix of location-scale models “sev”, “normal” and “logistic”. The function is also used to estimate the variance-covariance matrix of log-location-scale models with a threshold parameter, i.e. “weibull3”, “lognormal3” and “loglogistic3”.
- new argument in function ml_estimation(): wts for case weights.