R interface to access the web services of the ICES (International
             Council for the Exploration of the Sea) DATRAS trawl survey
             database <https://datras.ices.dk/WebServices/Webservices.aspx>.

Functions to Interact with the ICES Data Submission Utility (DATSU)
  <https://datsu.ices.dk/web/index.aspx>.

Run quality checks on data sets using the same checks that are conducted
  on the ICES Data Submission Utility (DATSU) <https://datsu.ices.dk>.

R interface to access the web services of the ICES Stock Assessment
             Graphs database <https://sg.ices.dk>.

R interface to access the web services of the ICES Stock Database <https://sd.ices.dk>.

Functions to support the ICES Transparent Assessment Framework
  <https://taf.ices.dk> to organize data, methods, and results used in ICES
  assessments. ICES is an organization facilitating international collaboration
  in marine science.

R interface to access the Vocabularies REST API of the ICES
  (International Council for the Exploration of the Sea) Vocabularies database
  <https://vocab.ices.dk/services/>.

It is a package that helps to estimate the number of real clusters in data as well as to identify atypical units. The underlying methods are based on distances rather than on unit x variables.

Calculate various information criteria in literature for "lm" and "glm" objects.

Generalized Odds Rate Hazards (GORH) model is a flexible model of fitting survival data, including the Proportional Hazards (PH) model and the Proportional Odds (PO) Model as special cases. This package fit the GORH model with interval censored data.

A GUI designed to support the analysis of financial-economic time
    series data.

We consider the non-parametric maximum likelihood estimation of the underlying distribution function, assuming log-concavity, based on mixed-case interval-censored data. The algorithm implemented is base on Chi Wing Chu, Hok Kan Ling and Chaoyu Yuan (2024, <doi:10.48550/arXiv.2411.19878>).

A variational Bayesian approach for fast integrative
    clustering and feature selection, facilitating the analysis of
    multi-view, mixed type, high-dimensional datasets with applications in
    fields like cancer research, genomics, and more.