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r-guerry
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This package comprises maps of France in 1830, multivariate data from A.-M. Guerry and others, and statistical and graphic methods related to Guerry's "Moral Statistics of France". The goal is to facilitate the exploration and development of statistical and graphic methods for multivariate data in a geo-spatial context of historical interest.
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2025-04-22 |
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r-guardianr
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Provides an interface to the Open Platform's Content API of the Guardian Media Group. It retrieves content from news outlets The Observer, The Guardian, and guardian.co.uk from 1999 to current day.
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2025-04-22 |
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r-gtx
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Assorted tools for genetic association analyses. The current focus is on implementing (either exactly or approximately) regression analyses using summary statistics instead of using subject-specific data. So far, functions exist to support multi-SNP risk score analyses, multi-SNP conditional regression analyses, and multi-phenotype analyses, using summary statistics. There are helper functions for reading and manipulating subject-specific genotype data, which provide a platform for calculating the summary statistics, or for using R to conduct other analyses not supported by specific GWAS analysis tools.
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2025-04-22 |
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r-gtwas
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Quantitative trait loci mapping and genome wide association analysis are used to find candidate molecular marker or region associated with phenotype based on linkage analysis and linkage disequilibrium. Gene expression quantitative trait loci mapping is used to find candidate molecular marker or region associated with gene expression. In this package, we applied the method in Liu W. (2011) <doi:10.1007/s00122-011-1631-7> and Gusev A. (2016) <doi:10.1038/ng.3506> to genome and transcriptome wide association study, which is aimed at revealing the association relationship between phenotype and molecular markers, expression levels, molecular markers nested within different related expression effect and expression effect nested within different related molecular marker effect. F test based on full and reduced model are performed to obtain p value or likelihood ratio statistic. The best linear model can be obtained by stepwise regression analysis.
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2025-04-22 |
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r-gtheory
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Estimates variance components, generalizability coefficients, universe scores, and standard errors when observed scores contain variation from one or more measurement facets (e.g., items and raters).
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2025-04-22 |
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r-gtests
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Four graph-based tests are provided for testing whether two samples are from the same distribution. It works for both continuous data and discrete data.
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2025-04-22 |
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r-gtcorr
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This package provides functions to calculate the efficiencies (expected tests per unit) of hierarchical and matrix group testing procedures. Efficiencies can be calculated in the presense of correlated responses under multiple arrangements of clustesrs. Efficiencies can also be evaluated in the presense of test error.
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2025-04-22 |
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r-gt4ireval
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Provides tools to measure the reliability of an Information Retrieval test collection. It allows users to estimate reliability using Generalizability Theory and map those estimates onto well-known indicators such as Kendall tau correlation or sensitivity.
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2025-04-22 |
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r-gsubfn
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The gsubfn function is like gsub but can take a replacement function or certain other objects instead of the replacement string. Matches and back references are input to the replacement function and replaced by the function output. gsubfn can be used to split strings based on content rather than delimiters and for quasi-perl-style string interpolation. The package also has facilities for translating formulas to functions and allowing such formulas in function calls instead of functions. This can be used with R functions such as apply, sapply, lapply, optim, integrate, xyplot, Filter and any other function that expects another function as an input argument or functions like cat or sql calls that may involve strings where substitution is desirable. There is also a facility for returning multiple objects from functions and a version of transform that allows the RHS to refer to LHS used in the same transform.
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2025-04-22 |
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r-gstream
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Uses an approach based on k-nearest neighbor information to sequentially detect change-points. Offers analytic approximations for false discovery control given user-specified average run length. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available. See references (1) Chen, H. (2019) Sequential change-point detection based on nearest neighbors. The Annals of Statistics, 47(3):1381-1407. (2) Chu, L. and Chen, H. (2018) Sequential change-point detection for high-dimensional and non-Euclidean data <arXiv:1810.05973>.
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2025-04-22 |
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r-gsmx
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Estimating trait heritability and handling overfitting. This package includes a collection of functions for (1) estimating genetic variance-covariances and calculate trait heritability; and (2) handling overfitting by calculating the variance components and the heritability through cross validation.
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2025-04-22 |
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r-gsm
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Implementation of a Bayesian approach for estimating a mixture of gamma distributions in which the mixing occurs over the shape parameter. This family provides a flexible and novel approach for modeling heavy-tailed distributions, it is computationally efficient, and it only requires to specify a prior distribution for a single parameter.
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2025-04-22 |
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r-gsloid
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Contains published data sets for global benthic d18O data for 0-5.3 Myr <doi:10.1029/2004PA001071> and global sea levels based on marine sediment core data for 0-800 ka <doi:10.5194/cp-12-1-2016>.
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2025-04-22 |
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r-gsheet
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Simple package to download Google Sheets using just the sharing link. Spreadsheets can be downloaded as a data frame, or as plain text to parse manually. Google Sheets is the new name for Google Docs Spreadsheets.
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2025-04-22 |
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r-gsg
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gsg (gam selection gradients) provides a unified approach to the regression analysis of selection from longitudinal data collected from natural populations.
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2025-04-22 |
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r-gseg
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Using an approach based on similarity graph to estimate change-point(s) and the corresponding p-values. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available.
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2025-04-22 |
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r-gsarima
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Write SARIMA models in (finite) AR representation and simulate generalized multiplicative seasonal autoregressive moving average (time) series with Normal / Gaussian, Poisson or negative binomial distribution.
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2025-04-22 |
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r-gsaq
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Computation of Quantitative Trait Loci hits in the selected gene set. Performing gene set validation with Quantitative Trait Loci information. Performing gene set enrichment analysis with available Quantitative Trait Loci data and computation of statistical significance value from gene set analysis. Obtaining the list of Quantitative Trait Loci hit genes along with their overlapped Quantitative Trait Loci names.
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2025-04-22 |
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r-gsalib
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This package contains utility functions used by the Genome Analysis Toolkit (GATK) to load tables and plot data. The GATK is a toolkit for variant discovery in high-throughput sequencing data.
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2025-04-22 |
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r-gsafishercombined
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Provides the p-value for a joint test of association between a phenotype and a set of genetic variants (SNPs) by combining marginal p-values using the Fisher method. See Fisher, R.A. (1925,ISBN:0-05-002170-2) Statistical Methods for Research Workers.
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2025-04-22 |
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r-gsa
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Gene Set Analysis.
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2025-04-22 |
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r-grto
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Offers functions for the comparison of Gutenberg-Richter b-values. Several functions in GRTo are helpful for the assessment of the quality of seismicity catalogs.
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2025-04-22 |
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r-grt
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Functions to generate and analyze data for psychology experiments based on the General Recognition Theory.
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2025-04-22 |
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r-grs.test
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Computational resources for test proposed by Gibbons, Ross, Shanken (1989)<DOI:10.2307/1913625>. It also has the functions for the power analysis and the choice of the optimal level of significance. The optimal level is determined by minimizing the expected loss from hypothesis testing.
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2025-04-22 |
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r-grpstring
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Methods include converting series of event names to strings, finding common patterns in a group of strings, discovering featured patterns when comparing two groups of strings as well as the number and starting position of each pattern in each string, obtaining transition matrix, computing transition entropy, statistically comparing the difference between two groups of strings, and clustering string groups. Event names can be any action names or labels such as events in log files or areas of interest (AOIs) in eye tracking research.
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2025-04-22 |
