Simulate Congruence Class Model for Networks
Ravi Goyal, with contributions from Mark S. Handcock (ergm R package), David R. Hunter (ergm R package), Carter T. Butts (ergm R package), Steven M. Goodreau (ergm R package), Pavel N. Krivitsky (ergm R package), Martina Morris (ergm R package), Nicole Bohme Carnegie (ergm-user term degmix)
Tools to simulate networks based on Congruence Class models.

Clustering through "Correlation Clustering Model" (CCM) and
cluster analysis tools.
R (>= 1.8.0), mclust, class, tree,mvtnorm
This package proposes a clustering method called
"Correlation Clustering Model" (CCM) based on mixture of
canonical correlation analysis (CCA). It also provides some
tools for cluster analysis.

Significance Tests for Canonical Correlation Analysis (CCA)
Significance tests for canonical correlation analysis,
including asymptotic tests and a Monte Carlo method

Significance tests are provided for canonical correlation analysis, including asymptotic tests and a Monte Carlo method.

Cultural Consensus Theory applications to data
A user-friendly GUI for the application of Cultural Consensus Theory (CCT) models and methods to consensus data. The models are applied using hierarchical Bayesian inference. The current package version supports binary, ordinal, and continuous data formats.
psych, mvtnorm, polycor, cluster, R2jags, rjags, tcltk

tcltk, rjags, R2jags, psych, mvtnorm, polycor

tcltk, rjags, psych, mvtnorm, polycor, MASS

tcltk, rjags, psych, mvtnorm, polycor, MASS, methods

Consensus Analysis, Model-Based Clustering, and Cultural
Consensus Theory Applications
Consensus analysis, model-based clustering, and cultural consensus theory applications to response data (e.g. questionnaires). The models are applied using hierarchical Bayesian inference. The current package version supports binary, ordinal, and continuous data formats.

Perform Weighted Linear Regression for Calibration Curve
Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve.
In addition, a 'shiny' App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements.
plotly, dplyr, stats, magrittr, shiny, bs4Dash, fresh, DT,
tools, readxl, rmarkdown, readr