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r-binhf
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public |
Binomial Haar-Fisz transforms for Gaussianization as in Nunes and Nason (2009).
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2025-04-22 |
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r-assertive.base
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public |
A minimal set of predicates and assertions used by the assertive package. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2025-04-22 |
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pytest-tornado
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public |
A py.test plugin providing fixtures and markers to simplify testing of
asynchronous tornado applications.
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2025-04-22 |
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r-entropy
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public |
This package implements various estimators of entropy, such as the shrinkage estimator by Hausser and Strimmer, the maximum likelihood and the Millow-Madow estimator, various Bayesian estimators, and the Chao-Shen estimator. It also offers an R interface to the NSB estimator. Furthermore, it provides functions for estimating Kullback-Leibler divergence, chi-squared, mutual information, and chi-squared statistic of independence. In addition there are functions for discretizing continuous random variables.
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2025-04-22 |
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r-adlift
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public |
Adaptive wavelet lifting transforms for signal denoising using optimal local neighbourhood regression, from Nunes et al. (2006) <doi:10.1007/s11222-006-6560-y>.
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2025-04-22 |
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xmlrunner
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public |
PyUnit-based test runner with JUnit like XML reporting.
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2025-04-22 |
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r-ebayesthresh
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public |
Empirical Bayes thresholding using the methods developed by I. M. Johnstone and B. W. Silverman. The basic problem is to estimate a mean vector given a vector of observations of the mean vector plus white noise, taking advantage of possible sparsity in the mean vector. Within a Bayesian formulation, the elements of the mean vector are modelled as having, independently, a distribution that is a mixture of an atom of probability at zero and a suitable heavy-tailed distribution. The mixing parameter can be estimated by a marginal maximum likelihood approach. This leads to an adaptive thresholding approach on the original data. Extensions of the basic method, in particular to wavelet thresholding, are also implemented within the package.
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2025-04-22 |
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r-ipred
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public |
Improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.
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2025-04-22 |
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r-chemometrics
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public |
R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009).
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2025-04-22 |
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r-pls
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public |
Multivariate regression methods Partial Least Squares Regression (PLSR), Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS).
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2025-04-22 |
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r-lava
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public |
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 (2019) <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.
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2025-04-22 |
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r-snftool
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public |
Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, and classification.
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2025-04-22 |
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r-rsvd
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public |
Low-rank matrix decompositions are fundamental tools and widely used for data analysis, dimension reduction, and data compression. Classically, highly accurate deterministic matrix algorithms are used for this task. However, the emergence of large-scale data has severely challenged our computational ability to analyze big data. The concept of randomness has been demonstrated as an effective strategy to quickly produce approximate answers to familiar problems such as the singular value decomposition (SVD). The rsvd package provides several randomized matrix algorithms such as the randomized singular value decomposition (rsvd), randomized principal component analysis (rpca), randomized robust principal component analysis (rrpca), randomized interpolative decomposition (rid), and the randomized CUR decomposition (rcur). In addition several plot functions are provided. The methods are discussed in detail by Erichson et al. (2016) <arXiv:1608.02148>.
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2025-04-22 |
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r-rknn
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public |
Random knn classification and regression are implemented. Random knn based feature selection methods are also included. The approaches are mainly developed for high-dimensional data with small sample size.
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2025-04-22 |
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r-lpsolve
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public |
Lp_solve is freely available (under LGPL 2) software for solving linear, integer and mixed integer programs. In this implementation we supply a "wrapper" function in C and some R functions that solve general linear/integer problems, assignment problems, and transportation problems. This version calls lp_solve version 5.5.
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2025-04-22 |
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r-ggcorrplot
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public |
The 'ggcorrplot' package can be used to visualize easily a correlation matrix using 'ggplot2'. It provides a solution for reordering the correlation matrix and displays the significance level on the plot. It also includes a function for computing a matrix of correlation p-values.
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2025-04-22 |
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r-plotroc
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public |
Most ROC curve plots obscure the cutoff values and inhibit interpretation and comparison of multiple curves. This attempts to address those shortcomings by providing plotting and interactive tools. Functions are provided to generate an interactive ROC curve plot for web use, and print versions. A Shiny application implementing the functions is also included.
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2025-04-22 |
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r-liftr
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public |
Persistent reproducible reporting by containerization of R Markdown documents.
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2025-04-22 |
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r-ggraph
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public |
The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. ggraph is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.
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2025-04-22 |
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r-genalg
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public |
R based genetic algorithm for binary and floating point chromosomes.
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2025-04-22 |
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pyemojify
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public |
Substitutes emoji aliases to emoji raw characters. Simple but sweet :smile:
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2025-04-22 |
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librsvg
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public |
librsvg is a library to render SVG files using cairo.
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2025-04-22 |
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pygsp
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public |
Graph Signal Processing in Python
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2025-04-22 |
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omas
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public |
Ordered Multidimensional Array Structure
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2025-04-22 |
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pyunlocbox
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public |
Convex Optimization in Python using Proximal Splitting
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2025-04-22 |
