Showing 200 of total 1475 results (show query)

elbersb

tidylog:Logging for 'dplyr' and 'tidyr' Functions

Provides feedback about 'dplyr' and 'tidyr' operations.

Maintained by Benjamin Elbers. Last updated 9 months ago.

dplyrtidyrtidyversewrapper-functions

127.5 match 593 stars 10.23 score 1.7k scripts

ecpolley

SuperLearner:Super Learner Prediction

Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.

Maintained by Eric Polley. Last updated 1 years ago.

39.6 match 274 stars 12.85 score 2.1k scripts 36 dependents

berndbischl

BBmisc:Miscellaneous Helper Functions for B. Bischl

Miscellaneous helper functions for and from B. Bischl and some other guys, mainly for package development.

Maintained by Bernd Bischl. Last updated 2 years ago.

26.5 match 20 stars 10.59 score 980 scripts 69 dependents

bioc

mixOmics:Omics Data Integration Project

Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares.

Maintained by Eva Hamrud. Last updated 3 days ago.

immunooncologymicroarraysequencingmetabolomicsmetagenomicsproteomicsgenepredictionmultiplecomparisonclassificationregressionbioconductorgenomicsgenomics-datagenomics-visualizationmultivariate-analysismultivariate-statisticsomicsr-pkgr-project

11.9 match 182 stars 13.71 score 1.3k scripts 22 dependents

miraisolutions

XLConnect:Excel Connector for R

Provides comprehensive functionality to read, write and format Excel data.

Maintained by Martin Studer. Last updated 17 days ago.

cross-platformexcelr-languagexlconnectopenjdk

6.9 match 130 stars 12.28 score 1.2k scripts 1 dependents

open-eo

openeo:Client Interface for 'openEO' Servers

Access data and processing functionalities of 'openEO' compliant back-ends in R.

Maintained by Florian Lahn. Last updated 2 months ago.

openeoopeneo-user

8.3 match 64 stars 8.65 score 128 scripts

robinhankin

gsl:Wrapper for the Gnu Scientific Library

An R wrapper for some of the functionality of the Gnu Scientific Library.

Maintained by Robin K. S. Hankin. Last updated 2 months ago.

gsl

5.6 match 15 stars 11.82 score 472 scripts 204 dependents

quanteda

spacyr:Wrapper to the 'spaCy' 'NLP' Library

An R wrapper to the 'Python' 'spaCy' 'NLP' library, from <https://spacy.io>.

Maintained by Kenneth Benoit. Last updated 1 months ago.

extract-entitiesnlpspacyspeech-tagging

5.5 match 253 stars 10.68 score 408 scripts 6 dependents

wikimedia

WikidataQueryServiceR:API Client Library for 'Wikidata Query Service'

An API client for the 'Wikidata Query Service' <https://query.wikidata.org/>.

Maintained by Mikhail Popov. Last updated 5 years ago.

api-wrappersparqlwdqswikidata

7.5 match 28 stars 7.67 score 73 scripts 31 dependents

nathaneastwood

gghalfnorm:Create a Half Normal Plot Using 'ggplot2'

Reproduce the halfnorm() function found in the 'faraway' package using the 'ggplot2' API.

Maintained by Nathan Eastwood. Last updated 8 years ago.

farawayggplot2-apiwrapper

11.0 match 2 stars 3.48 score 8 scripts 1 dependents

kss2k

modsem:Latent Interaction (and Moderation) Analysis in Structural Equation Models (SEM)

Estimation of interaction (i.e., moderation) effects between latent variables in structural equation models (SEM). The supported methods are: The constrained approach (Algina & Moulder, 2001). The unconstrained approach (Marsh et al., 2004). The residual centering approach (Little et al., 2006). The double centering approach (Lin et al., 2010). The latent moderated structural equations (LMS) approach (Klein & Moosbrugger, 2000). The quasi-maximum likelihood (QML) approach (Klein & Muthén, 2007) (temporarily unavailable) The constrained- unconstrained, residual- and double centering- approaches are estimated via 'lavaan' (Rosseel, 2012), whilst the LMS- and QML- approaches are estimated via 'modsem' it self. Alternatively model can be estimated via 'Mplus' (Muthén & Muthén, 1998-2017). References: Algina, J., & Moulder, B. C. (2001). <doi:10.1207/S15328007SEM0801_3>. "A note on estimating the Jöreskog-Yang model for latent variable interaction using 'LISREL' 8.3." Klein, A., & Moosbrugger, H. (2000). <doi:10.1007/BF02296338>. "Maximum likelihood estimation of latent interaction effects with the LMS method." Klein, A. G., & Muthén, B. O. (2007). <doi:10.1080/00273170701710205>. "Quasi-maximum likelihood estimation of structural equation models with multiple interaction and quadratic effects." Lin, G. C., Wen, Z., Marsh, H. W., & Lin, H. S. (2010). <doi:10.1080/10705511.2010.488999>. "Structural equation models of latent interactions: Clarification of orthogonalizing and double-mean-centering strategies." Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006). <doi:10.1207/s15328007sem1304_1>. "On the merits of orthogonalizing powered and product terms: Implications for modeling interactions among latent variables." Marsh, H. W., Wen, Z., & Hau, K. T. (2004). <doi:10.1037/1082-989X.9.3.275>. "Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction." Muthén, L.K. and Muthén, B.O. (1998-2017). "'Mplus' User’s Guide. Eighth Edition." <https://www.statmodel.com/>. Rosseel Y (2012). <doi:10.18637/jss.v048.i02>. "'lavaan': An R Package for Structural Equation Modeling."

Maintained by Kjell Solem Slupphaug. Last updated 9 days ago.

interaction-effectinteraction-effectslatent-moderated-structural-equationslavaan-syntaxlmsmoderationqmlquasi-maximum-likelihoodrlangrlanguagesemstructural-equation-modelingstructural-equation-modelsopenblascppopenmp

4.5 match 6 stars 8.42 score 54 scripts

ropensci

concstats:Market Structure, Concentration and Inequality Measures

Based on individual market shares of all participants in a market or space, the package offers a set of different structural and concentration measures frequently - and not so frequently - used in research and in practice. Measures can be calculated in groups or individually. The calculated measure or the resulting vector in table format should help practitioners make more informed decisions. Methods used in this package are from: 1. Chang, E. J., Guerra, S. M., de Souza Penaloza, R. A. & Tabak, B. M. (2005) "Banking concentration: the Brazilian case". 2. Cobham, A. and A. Summer (2013). "Is It All About the Tails? The Palma Measure of Income Inequality". 3. Garcia Alba Idunate, P. (1994). "Un Indice de dominancia para el analisis de la estructura de los mercados". 4. Ginevicius, R. and S. Cirba (2009). "Additive measurement of market concentration" <doi:10.3846/1611-1699.2009.10.191-198>. 5. Herfindahl, O. C. (1950), "Concentration in the steel industry" (PhD thesis). 6. Hirschmann, A. O. (1945), "National power and structure of foreign trade". 7. Melnik, A., O. Shy, and R. Stenbacka (2008), "Assessing market dominance" <doi:10.1016/j.jebo.2008.03.010>. 8. Palma, J. G. (2006). "Globalizing Inequality: 'Centrifugal' and 'Centripetal' Forces at Work". 9. Shannon, C. E. (1948). "A Mathematical Theory of Communication". 10. Simpson, E. H. (1949). "Measurement of Diversity" <doi:10.1038/163688a0>.

Maintained by Andreas Schneider. Last updated 1 years ago.

business-analyticscompetitionconcentrationdiversityinequalitypackage-development

7.0 match 7 stars 5.02 score 15 scripts

r-forge

RobAStBase:Robust Asymptotic Statistics

Base S4-classes and functions for robust asymptotic statistics.

Maintained by Matthias Kohl. Last updated 2 months ago.

7.0 match 4.96 score 64 scripts 4 dependents

topepo

caret:Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Maintained by Max Kuhn. Last updated 3 months ago.

1.8 match 1.6k stars 19.24 score 61k scripts 303 dependents