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kkholst

lava:Latent Variable Models

A general implementation of Structural Equation Models with latent variables (MLE, 2SLS, and composite likelihood estimators) with both continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>). Mixture latent variable models and non-linear latent variable models (Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>). The package also provides methods for graph exploration (d-separation, back-door criterion), simulation of general non-linear latent variable models, and estimation of influence functions for a broad range of statistical models.

Maintained by Klaus K. Holst. Last updated 3 months ago.

latent-variable-modelssimulationstatisticsstructural-equation-models

33 stars 12.87 score 610 scripts 478 dependents

mlr-org

mlr3pipelines:Preprocessing Operators and Pipelines for 'mlr3'

Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.

Maintained by Martin Binder. Last updated 27 days ago.

baggingdata-sciencedataflow-programmingensemble-learningmachine-learningmlr3pipelinespreprocessingstacking

141 stars 12.36 score 448 scripts 7 dependents

vosonlab

vosonSML:Collecting Social Media Data and Generating Networks for Analysis

A suite of easy to use functions for collecting social media data and generating networks for analysis. Supports Mastodon, YouTube, Reddit and Web 1.0 data sources.

Maintained by Bryan Gertzel. Last updated 9 months ago.

hyperlinkmastodonnetwork-graphredditsnasocial-mediasocial-network-analysisvosonyoutube

79 stars 7.67 score 66 scripts 1 dependents

ajsims1704

rdecision:Decision Analytic Modelling in Health Economics

Classes and functions for modelling health care interventions using decision trees and semi-Markov models. Mechanisms are provided for associating an uncertainty distribution with each source variable and for ensuring transparency of the mathematical relationships between variables. The package terminology follows Briggs "Decision Modelling for Health Economic Evaluation" (2006, ISBN:978-0-19-852662-9).

Maintained by Andrew Sims. Last updated 2 months ago.

3 stars 6.46 score 22 scripts

barbarabodinier

sharp:Stability-enHanced Approaches using Resampling Procedures

In stability selection (N Meinshausen, P Bühlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>) and consensus clustering (S Monti et al (2003) <doi:10.1023/A:1023949509487>), resampling techniques are used to enhance the reliability of the results. In this package (B Bodinier et al (2025) <doi:10.18637/jss.v112.i05>), hyper-parameters are calibrated by maximising model stability, which is measured under the null hypothesis that all selection (or co-membership) probabilities are identical (B Bodinier et al (2023a) <doi:10.1093/jrsssc/qlad058> and B Bodinier et al (2023b) <doi:10.1093/bioinformatics/btad635>). Functions are readily implemented for the use of LASSO regression, sparse PCA, sparse (group) PLS or graphical LASSO in stability selection, and hierarchical clustering, partitioning around medoids, K means or Gaussian mixture models in consensus clustering.

Maintained by Barbara Bodinier. Last updated 9 days ago.

13 stars 4.91 score 124 scripts

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