Showing 13 of total 13 results (show query)
alexkz
kernlab:Kernel-Based Machine Learning Lab
Kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods 'kernlab' includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.
Maintained by Alexandros Karatzoglou. Last updated 8 months ago.
21 stars 12.26 score 7.8k scripts 487 dependents
mschubert
clustermq:Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)
Evaluate arbitrary function calls using workers on HPC schedulers in single line of code. All processing is done on the network without accessing the file system. Remote schedulers are supported via SSH.
Maintained by Michael Schubert. Last updated 12 days ago.
clusterhigh-performance-computinglsfsgeslurmsshzeromq3cpp
149 stars 10.11 score 253 scripts
robinhankin
partitions:Additive Partitions of Integers
Additive partitions of integers. Enumerates the partitions, unequal partitions, and restricted partitions of an integer; the three corresponding partition functions are also given. Set partitions and now compositions and riffle shuffles are included.
Maintained by Robin K. S. Hankin. Last updated 7 months ago.
9 stars 10.04 score 191 scripts 78 dependents
jeromeecoac
seewave:Sound Analysis and Synthesis
Functions for analysing, manipulating, displaying, editing and synthesizing time waves (particularly sound). This package processes time analysis (oscillograms and envelopes), spectral content, resonance quality factor, entropy, cross correlation and autocorrelation, zero-crossing, dominant frequency, analytic signal, frequency coherence, 2D and 3D spectrograms and many other analyses. See Sueur et al. (2008) <doi:10.1080/09524622.2008.9753600> and Sueur (2018) <doi:10.1007/978-3-319-77647-7>.
Maintained by Jerome Sueur. Last updated 1 years ago.
18 stars 8.88 score 880 scripts 23 dependents
bioc
LEA:LEA: an R package for Landscape and Ecological Association Studies
LEA is an R package dedicated to population genomics, landscape genomics and genotype-environment association tests. LEA can run analyses of population structure and genome-wide tests for local adaptation, and also performs imputation of missing genotypes. The package includes statistical methods for estimating ancestry coefficients from large genotypic matrices and for evaluating the number of ancestral populations (snmf). It performs statistical tests using latent factor mixed models for identifying genetic polymorphisms that exhibit association with environmental gradients or phenotypic traits (lfmm2). In addition, LEA computes values of genetic offset statistics based on new or predicted environments (genetic.gap, genetic.offset). LEA is mainly based on optimized programs that can scale with the dimensions of large data sets.
Maintained by Olivier Francois. Last updated 19 days ago.
softwarestatistical methodclusteringregressionopenblas
6.63 score 534 scripts
bendeivide
leem:Laboratory of Teaching to Statistics and Mathematics
An educational package for teaching statistics and mathematics in both primary and higher education. The objective is to assist in the teaching/learning process, both for student study planning and teacher teaching strategies. The leem package aims to provide, in a simple yet in-depth manner, knowledge of statistics and mathematics to anyone who wants to study these areas of knowledge.
Maintained by Ben Deivide. Last updated 2 days ago.
4 stars 5.44 score 152 scripts
guokai8
o2plsda:Multiomics Data Integration
Provides functions to do 'O2PLS-DA' analysis for multiple omics data integration. The algorithm came from "O2-PLS, a two-block (X±Y) latent variable regression (LVR) method with an integral OSC filter" which published by Johan Trygg and Svante Wold at 2003 <doi:10.1002/cem.775>. 'O2PLS' is a bidirectional multivariate regression method that aims to separate the covariance between two data sets (it was recently extended to multiple data sets) (Löfstedt and Trygg, 2011 <doi:10.1002/cem.1388>; Löfstedt et al., 2012 <doi:10.1016/j.aca.2013.06.026>) from the systematic sources of variance being specific for each data set separately.
Maintained by Kai Guo. Last updated 1 months ago.
integrationmulti-omicso2plsomicsplsdaopenblascppopenmp
7 stars 5.02 score 6 scripts
alexchristensen
SemNeT:Methods and Measures for Semantic Network Analysis
Implements several functions for the analysis of semantic networks including different network estimation algorithms, partial node bootstrapping (Kenett, Anaki, & Faust, 2014 <doi:10.3389/fnhum.2014.00407>), random walk simulation (Kenett & Austerweil, 2016 <http://alab.psych.wisc.edu/papers/files/Kenett16CreativityRW.pdf>), and a function to compute global network measures. Significance tests and plotting features are also implemented.
Maintained by Alexander P. Christensen. Last updated 2 years ago.
23 stars 4.51 score 28 scripts
jhhmuc
pairwise:Rasch Model Parameters by Pairwise Algorithm
Performs the explicit calculation -- not estimation! -- of the Rasch item parameters for dichotomous and polytomous item responses, using a pairwise comparison approach. Person parameters (WLE) are calculated according to Warm's weighted likelihood approach.
Maintained by Joerg-Henrik Heine. Last updated 2 years ago.
3.96 score 38 scripts 1 dependents
hanel
musica:Multiscale Climate Model Assessment
Provides functions allowing for (1) easy aggregation of multivariate time series into custom time scales, (2) comparison of statistical summaries between different data sets at multiple time scales (e.g. observed and bias-corrected data), (3) comparison of relations between variables and/or different data sets at multiple time scales (e.g. correlation of precipitation and temperature in control and scenario simulation) and (4) transformation of time series at custom time scales.
Maintained by Martin Hanel. Last updated 8 years ago.
3.85 score 14 scripts
cran
colourvision:Colour Vision Models
Colour vision models, colour spaces and colour thresholds. Provides flexibility to build user-defined colour vision models for n number of photoreceptor types. Includes Vorobyev & Osorio (1998) Receptor Noise Limited models <doi:10.1098/rspb.1998.0302>, Chittka (1992) colour hexagon <doi:10.1007/BF00199331>, and Endler & Mielke (2005) model <doi:10.1111/j.1095-8312.2005.00540.x>. Models have been extended to accept any number of photoreceptor types.
Maintained by Felipe Malheiros Gawryszewski. Last updated 3 months ago.
2.30 score
artemiszhao
PRP:Bayesian Prior and Posterior Predictive Replication Assessment
Utilize the Bayesian prior and posterior predictive checking approach to provide a statistical assessment of replication success and failure. The package is based on the methods proposed in Zhao,Y., Wen X.(2021) <arXiv:2105.03993>.
Maintained by Yi Zhao. Last updated 3 years ago.
2.30 score 3 scriptscran
SpatialVx:Spatial Forecast Verification
Spatial forecast verification refers to verifying weather forecasts when the verification set (forecast and observations) is on a spatial field, usually a high-resolution gridded spatial field. Most of the functions here require the forecast and observed fields to be gridded and on the same grid. For a thorough review of most of the methods in this package, please see Gilleland et al. (2009) <doi: 10.1175/2009WAF2222269.1> and for a tutorial on some of the main functions available here, see Gilleland (2022) <doi: 10.5065/4px3-5a05>.
Maintained by Eric Gilleland. Last updated 4 months ago.
1 stars 1.00 score