gamlr - Gamma Lasso Regression
The gamma lasso algorithm provides regularization paths corresponding to a range of non-convex cost functions between L0 and L1 norms. As much as possible, usage for this package is analogous to that for the glmnet package (which does the same thing for penalization between L1 and L2 norms). For details see: Taddy (2017 JCGS), 'One-Step Estimator Paths for Concave Regularization', <doi:10.48550/arXiv.1308.5623>.
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7.77 score 23 stars 5 dependents 343 scripts 761 downloadsmaptpx - MAP Estimation of Topic Models
Maximum a posteriori (MAP) estimation for topic models (i.e., Latent Dirichlet Allocation) in text analysis, as described in Taddy (2012) 'On estimation and selection for topic models'. Previous versions of this code were included as part of the 'textir' package. If you want to take advantage of openmp parallelization, uncomment the relevant flags in src/MAKEVARS before compiling.
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map-estimationtopic-modelingopenblas
6.27 score 19 stars 2 dependents 327 scripts 494 downloadsdistrom - Distributed Multinomial Regression
Fast distributed/parallel estimation for multinomial logistic regression via Poisson factorization and the 'gamlr' package. For details see: Taddy (2015, AoAS), Distributed Multinomial Regression, <doi:10.48550/arXiv.1311.6139>.
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6.18 score 20 stars 3 dependents 56 scripts 461 downloadstextir - Inverse Regression for Text Analysis
Multinomial (inverse) regression inference for text documents and associated attributes. For details see: Taddy (2013 JASA) Multinomial Inverse Regression for Text Analysis <arXiv:1012.2098> and Taddy (2015, AoAS), Distributed Multinomial Regression, <arXiv:1311.6139>. A minimalist partial least squares routine is also included. Note that the topic modeling capability of earlier 'textir' is now a separate package, 'maptpx'.
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6.11 score 30 stars 2 dependents 143 scripts 520 downloads