R-universe search: exports:corr

Showing 12 of total 12 results (show query)

laresbernardo

lares:Analytics & Machine Learning Sidekick

Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, Marketing Mix Modeling (Robyn), Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or advanced R programming skills.

Maintained by Bernardo Lares. Last updated 1 months ago.

analytics api automation automl data-science descriptive-statistics h2o machine-learning marketing mmm predictive-modeling puzzle rlanguage robyn visualization

233 stars 9.92 score 185 scripts 1 dependents

bioc

iCOBRA:Comparison and Visualization of Ranking and Assignment Methods

This package provides functions for calculation and visualization of performance metrics for evaluation of ranking and binary classification (assignment) methods. Various types of performance plots can be generated programmatically. The package also contains a shiny application for interactive exploration of results.

Maintained by Charlotte Soneson. Last updated 3 months ago.

classification visualization

16 stars 8.84 score 192 scripts 1 dependents

robinhankin

emulator:Bayesian Emulation of Computer Programs

Allows one to estimate the output of a computer program, as a function of the input parameters, without actually running it. The computer program is assumed to be a Gaussian process, whose parameters are estimated using Bayesian techniques that give a PDF of expected program output. This PDF is conditional on a training set of runs, each consisting of a point in parameter space and the model output at that point. The emphasis is on complex codes that take weeks or months to run, and that have a large number of undetermined input parameters; many climate prediction models fall into this class. The emulator essentially determines Bayesian posterior estimates of the PDF of the output of a model, conditioned on results from previous runs and a user-specified prior linear model. The package includes functionality to evaluate quadratic forms efficiently.

Maintained by Robin K. S. Hankin. Last updated 9 months ago.

4 stars 8.27 score 56 scripts 17 dependents

cran

boot:Bootstrap Functions (Originally by Angelo Canty for S)

Functions and datasets for bootstrapping from the book "Bootstrap Methods and Their Application" by A. C. Davison and D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S.

Maintained by Alessandra R. Brazzale. Last updated 7 months ago.

2 stars 7.92 score 2.3k dependents

uscbiostats

partition:Agglomerative Partitioning Framework for Dimension Reduction

A fast and flexible framework for agglomerative partitioning. 'partition' uses an approach called Direct-Measure-Reduce to create new variables that maintain the user-specified minimum level of information. Each reduced variable is also interpretable: the original variables map to one and only one variable in the reduced data set. 'partition' is flexible, as well: how variables are selected to reduce, how information loss is measured, and the way data is reduced can all be customized. 'partition' is based on the Partition framework discussed in Millstein et al. (2020) <doi:10.1093/bioinformatics/btz661>.

Maintained by Malcolm Barrett. Last updated 5 months ago.

data-reduction dimensionality-reduction partitional-clustering openblas cpp

36 stars 7.72 score 27 scripts 1 dependents

sachaepskamp

psychonetrics:Structural Equation Modeling and Confirmatory Network Analysis

Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data <doi:10.31234/osf.io/8ha93>. Allows for confirmatory testing and fit as well as exploratory model search.

Maintained by Sacha Epskamp. Last updated 6 days ago.

openblas cpp

51 stars 6.88 score 41 scripts 1 dependents

taddylab

textir: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'.

Maintained by Matt Taddy. Last updated 7 years ago.

29 stars 6.03 score 123 scripts 2 dependents

bioc

crlmm:Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays

Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 5.0, 6.0, and Illumina platforms.

Maintained by Benilton S Carvalho. Last updated 29 days ago.

microarray preprocessing snp copynumbervariation

4.78 score 37 scripts 3 dependents

chrisaberson

pwr2ppl:Power Analyses for Common Designs (Power to the People)

Statistical power analysis for designs including t-tests, correlations, multiple regression, ANOVA, mediation, and logistic regression. Functions accompany Aberson (2019) <doi:10.4324/9781315171500>.

Maintained by Chris Aberson. Last updated 3 years ago.

17 stars 4.16 score 17 scripts

adbecker

tsiR:An Implementation of the TSIR Model

An implementation of the time-series Susceptible-Infected-Recovered (TSIR) model using a number of different fitting options for infectious disease time series data. The manuscript based on this package can be found here <doi:10.1371/journal.pone.0185528>. The method implemented here is described by Finkenstadt and Grenfell (2000) <doi:10.1111/1467-9876.00187>.

Maintained by Alexander D. Becker. Last updated 4 years ago.

2.75 score 28 scripts

abeyrann

Path.Analysis:Path Coefficient Analysis

Facilitates the performance of several analyses, including simple and sequential path coefficient analysis, correlation estimate, drawing correlogram, Heatmap, and path diagram. When working with raw data, that includes one or more dependent variables along with one or more independent variables are available, the path coefficient analysis can be conducted. It allows for testing direct effects, which can be a vital indicator in path coefficient analysis. The process of preparing the dataset rule is explained in detail in the vignette file "Path.Analysis_manual.Rmd". You can find this in the folders labelled "data" and "~/inst/extdata". Also see: 1)the 'lavaan', 2)a sample of sequential path analysis in 'metan' suggested by Olivoto and Lúcio (2020) <doi:10.1111/2041-210X.13384>, 3)the simple 'PATHSAS' macro written in 'SAS' by Cramer et al. (1999) <doi:10.1093/jhered/90.1.260>, and 4)the semPlot() function of 'OpenMx' as initial tools for conducting path coefficient analyses and SEM (Structural Equation Modeling). To gain a comprehensive understanding of path coefficient analysis, both in theory and practice, see a 'Minitab' macro developed by Arminian, A. in the paper by Arminian et al. (2008) <doi:10.1080/15427520802043182>.

Maintained by Ali Arminian. Last updated 6 months ago.

2.70 score

kdpeterson51

mbir:Magnitude-Based Inferences

Allows practitioners and researchers a wholesale approach for deriving magnitude-based inferences from raw data. A major goal of 'mbir' is to programmatically detect appropriate statistical tests to run in lieu of relying on practitioners to determine correct stepwise procedures independently.

Maintained by Kyle Peterson. Last updated 6 years ago.

1 stars 2.48 score 15 scripts