Provides an application that acts as a GUI for the 'stm' text analysis package.

Implementation of the family of generalised age-period-cohort
    stochastic mortality models. This family of models encompasses many models
    proposed in the actuarial and demographic literature including the 
    Lee-Carter (1992) <doi:10.2307/2290201> and
    the Cairns-Blake-Dowd (2006) <doi:10.1111/j.1539-6975.2006.00195.x> models. 
    It includes functions for fitting mortality models, analysing their 
    goodness-of-fit and performing mortality projections and simulations.

Plots a QQ-Norm Plot with several Gaussian simulations.

Allow to identify motifs in spatial-time series. A motif is a previously unknown subsequence of a (spatial) time series with relevant number of occurrences. For this purpose, the Combined Series Approach (CSA) is used.

Strength training prescription using percent-based approach requires
    numerous computations and assumptions. 'STMr' package allow users to estimate 
    individual reps-max relationships, implement various progression tables, and
    create numerous set and rep schemes. The 'STMr' package is originally created as
    a tool to help writing Jovanović M. (2020) Strength Training Manual
    <ISBN:979-8604459898>.

Fit a spatial-temporal occupancy models using
    a probit formulation instead of a traditional logit
    model.

Stochastic blockmodeling of one-mode and linked networks as presented in Škulj and Žiberna (2022) <doi:10.1016/j.socnet.2022.02.001>. The optimization is done via CEM (Classification Expectation Maximization) algorithm that can be initialized by random partitions or the results of k-means algorithm. The development of this package is financially supported by the Slovenian Research Agency (<https://www.arrs.si/>) within the research programs P5-0168 and the research projects J7-8279 (Blockmodeling multilevel and temporal networks) and J5-2557 (Comparison and evaluation of different approaches to blockmodeling dynamic networks by simulations with application to Slovenian co-authorship networks).