Probability distributions that are sometimes useful in hydrology.

An implementation of a clustering algorithm for functional data based on adaptive density peak detection technique, in which the density is estimated by functional k-nearest neighbor density estimation based on a proposed semi-metric between functions. The proposed functional data clustering algorithm is computationally fast since it does not need iterative process. (Alex Rodriguez and Alessandro Laio (2014) <doi:10.1126/science.1242072>; Xiao-Feng Wang and Yifan Xu (2016) <doi:10.1177/0962280215609948>).

An easy framework to read FDA Adverse Event Reporting System XML/ASCII files <https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/fda-adverse-event-reporting-system-faers-latest-quarterly-data-files>.

This Shiny application offers researchers a comprehensive tool for performing factor analysis. Users can upload datasets, validate assumptions, manage missing and outlier data, split data for different analyses, and run exploratory and confirmatory factor analyses ("EFA" and "CFA"). The software also offers reliability analysis, exploratory graph analysis, and item weighting. With a user-friendly interface, this tool simplifies the EFA and CFA processes. The main features are data submission and simple data inspection. Data manipulation (excluding variables, splitting data, checking for outliers), assumption checking (Tabachnik & Fidell (2012) <ISBN:978-0-205-84957-4> and Field (2009) <ISBN:978-1-84787-906-6>) for factor analysis, exploratory factor analysis (with various factor number determination methods (Lorenzo-Seva & Ferrando (2021) <doi:10.5964/meth.7185>)), confirmatory factor analysis (model definition and modification suggestions (Kline (2011) <ISBN:978-1-60623-877-6>)), reliability analysis (Cronbach's alpha, McDonald's omega, Armor's theta, structural reliability, stratified alpha), item weighting (Kilic & Dogan (2019) <doi:10.21031/epod.516057>).

Data and functions for the book "Multivariate Statistical 
              Modelling Based on Generalized Linear Models", first edition, by 
              Ludwig Fahrmeir and Gerhard Tutz.  Useful when using the book.