r-featurehashing
|
public |
Feature hashing, also called as the hashing trick, is a method to transform features of a instance to a vector. Thus, it is a method to transform a real dataset to a matrix. Without looking up the indices in an associative array, it applies a hash function to the features and uses their hash values as indices directly. The method of feature hashing in this package was proposed in Weinberger et al. (2009) <arXiv:0902.2206>. The hashing algorithm is the murmurhash3 from the 'digest' package. Please see the README in <https://github.com/wush978/FeatureHashing> for more information.
|
2025-04-22 |
r-fdrtool
|
public |
Estimates both tail area-based false discovery rates (Fdr) as well as local false discovery rates (fdr) for a variety of null models (p-values, z-scores, correlation coefficients, t-scores). The proportion of null values and the parameters of the null distribution are adaptively estimated from the data. In addition, the package contains functions for non-parametric density estimation (Grenander estimator), for monotone regression (isotonic regression and antitonic regression with weights), for computing the greatest convex minorant (GCM) and the least concave majorant (LCM), for the half-normal and correlation distributions, and for computing empirical higher criticism (HC) scores and the corresponding decision threshold.
|
2025-04-22 |
r-fdamixed
|
public |
Likelihood based analysis of 1-dimension functional data in a mixed-effects model framework. Matrix computation are approximated by semi-explicit operator equivalents with linear computational complexity. Markussen (2013) <doi:10.3150/11-BEJ389>.
|
2025-04-22 |
r-fcros
|
public |
A fold change rank based method is presented to search for genes with changing expression and to detect recurrent chromosomal copy number aberrations. This method may be useful for high-throughput biological data (micro-array, sequencing, ...). Probabilities are associated with genes or probes in the data set and there is no problem of multiple tests when using this method. For array-based comparative genomic hybridization data, segmentation results are obtained by merging the significant probes detected.
|
2025-04-22 |
r-fclust
|
public |
Algorithms for fuzzy clustering, cluster validity indices and plots for cluster validity and visualizing fuzzy clustering results.
|
2025-04-22 |
r-fbfsearch
|
public |
We propose an objective Bayesian algorithm for searching the space of Gaussian directed acyclic graph (DAG) models. The algorithm proposed makes use of moment fractional Bayes factors (MFBF) and thus it is suitable for learning sparse graph. The algorithm is implemented by using Armadillo: an open-source C++ linear algebra library.
|
2025-04-22 |
r-fasttime
|
public |
Fast functions for timestamp manipulation that avoid system calls and take shortcuts to facilitate operations on very large data.
|
2025-04-22 |
r-fasttextr
|
public |
An interface to the 'fastText' library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. The install folder contains the 'PATENTS' file. An example how to use 'fastTextR' can be found in the 'README' file.
|
2025-04-22 |
r-fastsom
|
public |
Functions for computing spillover measures, especially spillover tables and spillover indices, as well as their average, minimal, and maximal values.
|
2025-04-22 |
r-fastrweb
|
public |
Infrastrcture for creating rich, dynamic web content using R scripts while maintaining very fast response time.
|
2025-04-22 |
r-fastrcs
|
public |
The FastRCS algorithm of Vakili and Schmitt (2014) for robust fit of the multivariable linear regression model and outliers detection.
|
2025-04-22 |
r-fastpcs
|
public |
The FastPCS algorithm of Vakili and Schmitt (2014) <doi:10.1016/j.csda.2013.07.021> for robust estimation of multivariate location and scatter and multivariate outliers detection.
|
2025-04-22 |
r-fastmatch
|
public |
Package providing a fast match() replacement for cases that require repeated look-ups. It is slightly faster that R's built-in match() function on first match against a table, but extremely fast on any subsequent lookup as it keeps the hash table in memory.
|
2025-04-22 |
r-fastmap
|
public |
Fast implementation of a key-value store. Environments are commonly used as key-value stores, but every time a new key is used, it is added to R's global symbol table, causing a small amount of memory leakage. This can be problematic in cases where many different keys are used. Fastmap avoids this memory leak issue by implementing the map using data structures in C++.
|
2025-04-22 |
r-fastm
|
public |
Implements the new algorithm for fast computation of M-scatter matrices using a partial Newton-Raphson procedure for several estimators. The algorithm is described in Duembgen, Nordhausen and Schuhmacher (2016) <doi:10.1016/j.jmva.2015.11.009>.
|
2025-04-22 |
r-fastlzerospikeinference
|
public |
Estimate spike times from calcium imaging data using an L0 penalty.
|
2025-04-22 |
r-fastjt
|
public |
This 'Rcpp'-based package implements highly efficient functions for the calculation of the Jonckheere-Terpstra statistic. It can be used for a variety of applications, including feature selection in machine learning problems, or to conduct genome-wide association studies (GWAS) with multiple quantitative phenotypes. The code leverages 'OpenMP' directives for multi-core computing to reduce overall processing time.
|
2025-04-22 |
r-fasthcs
|
public |
The FastHCS algorithm of Schmitt and Vakili (2014) <doi:10.1007/s11222-015-9602-5> for high-dimensional, robust PCA modelling and associated outlier detection and diagnostic tools.
|
2025-04-22 |
r-fastglm
|
public |
Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares implementation utilizes the step-halving approach of Marschner (2011) <doi:10.32614/RJ-2011-012> to help safeguard against convergence issues.
|
2025-04-22 |
r-fastghquad
|
public |
Fast, numerically-stable Gauss-Hermite quadrature rules and utility functions for adaptive GH quadrature. See Liu, Q. and Pierce, D. A. (1994) <doi:10.2307/2337136> for a reference on these methods.
|
2025-04-22 |
r-fasterize
|
public |
Provides a drop-in replacement for rasterize() from the 'raster' package that takes 'sf'-type objects, and is much faster. There is support for the main options provided by the rasterize() function, including setting the field used and background value, and options for aggregating multi-layer rasters. Uses the scan line algorithm attributed to Wylie et al. (1967) <doi:10.1145/1465611.1465619>.
|
2025-04-22 |
r-fasterelasticnet
|
public |
Fit Elastic Net, Lasso, and Ridge regression and do cross-validation in a fast way. We build the algorithm based on Least Angle Regression by Bradley Efron, Trevor Hastie, Iain Johnstone, etc. (2004)(<doi:10.1214/009053604000000067 >) and some algorithms like Givens rotation and Forward/Back Substitution. In this way, many matrices to be computed are retained as triangular matrices which can eventually speed up the computation. The fitting algorithm for Elastic Net is written in C++ using Armadillo linear algebra library.
|
2025-04-22 |
r-fasteraster
|
public |
If there is a need to recognise edges on a raster image or a bitmap or any kind of a matrix, one can find packages that does only 90 degrees vectorization. Typically the nature of artefact images is linear and can be vectorized in much more efficient way than draw a series of 90 degrees lines. The fasteraster package does recognition of lines using only one pass. It also allows to calculate mass and the mass centers for the recognized zones or polygons.
|
2025-04-22 |
r-fastdigest
|
public |
Provides an R interface to Bob Jenkin's streaming, non-cryptographic 'SpookyHash' hash algorithm for use in digest-based comparisons of R objects. 'fastdigest' plugs directly into R's internal serialization machinery, allowing digests of all R objects the serialize() function supports, including reference-style objects via custom hooks. Speed is high and scales linearly by object size; memory usage is constant and negligible.
|
2025-04-22 |
r-fastcox
|
public |
We implement a cocktail algorithm, a good mixture of coordinate decent, the majorization-minimization principle and the strong rule, for computing the solution paths of the elastic net penalized Cox's proportional hazards model. The package is an implementation of Yang, Y. and Zou, H. (2013) DOI: <doi:10.4310/SII.2013.v6.n2.a1>.
|
2025-04-22 |