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alinetalhouk

diceR:Diverse Cluster Ensemble in R

Performs cluster analysis using an ensemble clustering framework, Chiu & Talhouk (2018) <doi:10.1186/s12859-017-1996-y>. Results from a diverse set of algorithms are pooled together using methods such as majority voting, K-Modes, LinkCluE, and CSPA. There are options to compare cluster assignments across algorithms using internal and external indices, visualizations such as heatmaps, and significance testing for the existence of clusters.

Maintained by Derek Chiu. Last updated 2 months ago.

cpp

37 stars 8.13 score 60 scripts 3 dependents

kosugitti

exametrika:Test Theory Analysis and Biclustering

Implements comprehensive test data engineering methods as described in Shojima (2022, ISBN:978-9811699856). Provides statistical techniques for engineering and processing test data: Classical Test Theory (CTT) with reliability coefficients for continuous ability assessment; Item Response Theory (IRT) including Rasch, 2PL, and 3PL models with item/test information functions; Latent Class Analysis (LCA) for nominal clustering; Latent Rank Analysis (LRA) for ordinal clustering with automatic determination of cluster numbers; Biclustering methods including infinite relational models for simultaneous clustering of examinees and items without predefined cluster numbers; and Bayesian Network Models (BNM) for visualizing inter-item dependencies. Features local dependence analysis through LRA and biclustering, parameter estimation, dimensionality assessment, and network structure visualization for educational, psychological, and social science research.

Maintained by Koji Kosugi. Last updated 1 days ago.

1 stars 4.33 score 25 scripts

cran

nsRFA:Non-Supervised Regional Frequency Analysis

A collection of statistical tools for objective (non-supervised) applications of the Regional Frequency Analysis methods in hydrology. The package refers to the index-value method and, more precisely, helps the hydrologist to: (1) regionalize the index-value; (2) form homogeneous regions with similar growth curves; (3) fit distribution functions to the empirical regional growth curves. Most of the methods are those described in the Flood Estimation Handbook (Centre for Ecology & Hydrology, 1999, ISBN:9781906698003). Homogeneity tests from Hosking and Wallis (1993) <doi:10.1029/92WR01980> and Viglione et al. (2007) <doi:10.1029/2006WR005095> are available.

Maintained by Alberto Viglione. Last updated 11 months ago.

2 stars 3.48 score

edcurry

LCA:Localised Co-Dependency Analysis

Performs model fitting and significance estimation for Localised Co-Dependency between pairs of features of a numeric dataset.

Maintained by Ed Curry. Last updated 6 years ago.

2.00 score 4 scripts

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