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r-auditor
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public |
Provides an easy to use unified interface for creating validation plots for any model. The 'auditor' helps to avoid repetitive work consisting of writing code needed to create residual plots. This visualizations allow to asses and compare the goodness of fit, performance, and similarity of models.
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2024-01-16 |
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r-automl
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public |
Fits from simple regression to highly customizable deep neural networks either with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost function. A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization.
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2024-01-16 |
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r-augmentedrcbd
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public |
Functions for analysis of data generated from experiments in augmented randomised complete block design according to Federer, W.T. (1961) <doi:10.2307/2527837>. Computes analysis of variance, adjusted means, descriptive statistics, genetic variability statistics etc. Further includes data visualization and report generation functions.
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2024-01-16 |
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r-autodeskr
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public |
An interface to the 'AutoDesk' 'API' Platform including the Authentication 'API' for obtaining authentication to the 'AutoDesk' Forge Platform, Data Management 'API' for managing data across the platform's cloud services, Design Automation 'API' for performing automated tasks on design files in the cloud, Model Derivative 'API' for translating design files into different formats, sending them to the viewer app, and extracting design data, and Viewer for rendering 2D and 3D models (see <https://developer.autodesk.com> for more information).
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2024-01-16 |
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r-atr
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public |
Plot party trees in left-right orientation instead of the classical top-down layout.
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2024-01-16 |
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r-auto.pca
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public |
PCA done by eigenvalue decomposition of a data correlation matrix, here it automatically determines the number of factors by eigenvalue greater than 1 and it gives the uncorrelated variables based on the rotated component scores, Such that in each principal component variable which has the high variance are selected. It will be useful for non-statisticians in selection of variables. For more information, see the <http://www.ijcem.org/papers032013/ijcem_032013_06.pdf> web page.
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2024-01-16 |
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r-auth0
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public |
Uses Auth0 API (see <https://auth0.com> for more information) to use a simple authentication system. It provides tools to log in and out a shiny application using social networks or a list of e-mails.
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2024-01-16 |
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r-assetcorr
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public |
Functions for the estimation of intra- and inter-cohort correlations in the Vasicek credit portfolio model. For intra-cohort correlations, the package covers the two method of moments estimators of Gordy (2000) <doi:10.1016/S0378-4266(99)00054-0>, the method of moments estimator of Lucas (1995) <https://jfi.pm-research.com/content/4/4/76> and a Binomial approximation extension of this approach. Moreover, the maximum likelihood estimators of Gordy and Heitfield (2010) <http://elsa.berkeley.edu/~mcfadden/e242_f03/heitfield.pdf> and Duellmann and Gehde-Trapp (2004) <http://hdl.handle.net/10419/19729> are implemented. For inter-cohort correlations, the method of moments estimator of Bluhm and Overbeck (2003) <doi:10.1007/978-3-642-59365-9_2>/Bams et al. (2016) <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2676595> is provided and the maximum likelihood estimators comprise the approaches of Gordy and Heitfield (2010)/Kalkbrener and Onwunta (2010) <ISBN: 978-1906348250> and Pfeuffer et al. (2020). Bootstrap and Jackknife procedures for bias correction are included as well as the method of moments estimator of Frei and Wunsch (2018) <doi:10.21314/JCR.2017.231> for auto-correlated time series.
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2024-01-16 |
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r-audit
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public |
Find an upper bound for the total amount of overstatement of assets in a set of accounts, or estimate the amount of sales tax owed on a collection of transactions (Meeden and Sargent, 2007, <doi:10.1080/03610920701386802>).
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2024-01-16 |
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r-auc
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public |
Various functions to compute the area under the curve of selected measures: The area under the sensitivity curve (AUSEC), the area under the specificity curve (AUSPC), the area under the accuracy curve (AUACC), and the area under the receiver operating characteristic curve (AUROC). Support for visualization and partial areas is included.
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2024-01-16 |
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r-attempt
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public |
Tools for defensive programming, inspired by 'purrr' mappers and based on 'rlang'.'attempt' extends and facilitates defensive programming by providing a consistent grammar, and provides a set of easy to use functions for common tests and conditions. 'attempt' only depends on 'rlang', and focuses on speed, so it can be easily integrated in other functions and used in data analysis.
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2024-01-16 |
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r-attachment
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public |
Manage dependencies during package development. This can retrieve all dependencies that are used in ".R" files in the "R/" directory, in ".Rmd" files in "vignettes/" directory and in 'roxygen2' documentation of functions. There is a function to update the "DESCRIPTION" file of your package with 'CRAN' packages or any other remote package. All functions to retrieve dependencies of ".R" scripts and ".Rmd" or ".qmd" files can be used independently of a package development.
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2024-01-16 |
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r-asynchlong
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public |
Estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent response and covariates are mismatched and observed intermittently within subjects. Kernel weighted estimating equations are used for generalized linear models with either time-invariant or time-dependent coefficients. Cao, H., Li, J., and Fine, J. P. (2016) <doi:10.1214/16-EJS1141>. Cao, H., Zeng, D., and Fine, J. P. (2015) <doi:10.1111/rssb.12086>.
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2024-01-16 |
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r-atsa
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public |
Contains some tools for testing, analyzing time series data and fitting popular time series models such as ARIMA, Moving Average and Holt Winters, etc. Most functions also provide nice and clear outputs like SAS does, such as identify, estimate and forecast, which are the same statements in PROC ARIMA in SAS.
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2024-01-16 |
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r-atlas
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public |
Stanford 'ATLAS' (Advanced Temporal Search Engine) is a powerful tool that allows constructing cohorts of patients extremely quickly and efficiently. This package is designed to interface directly with an instance of 'ATLAS' search engine and facilitates API queries and data dumps. Prerequisite is a good knowledge of the temporal language to be able to efficiently construct a query. More information available at <https://shahlab.stanford.edu/start>.
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2024-01-16 |
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r-asymptest
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public |
One and two sample mean and variance tests (differences and ratios) are considered. The test statistics are all expressed in the same form as the Student t-test, which facilitates their presentation in the classroom. This contribution also fills the gap of a robust (to non-normality) alternative to the chi-square single variance test for large samples, since no such procedure is implemented in standard statistical software.
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2024-01-16 |
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r-asymld
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public |
Computes asymmetric LD measures (ALD) for multi-allelic genetic data. These measures are identical to the correlation measure (r) for bi-allelic data.
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2024-01-16 |
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r-assertr
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public |
Provides functionality to assert conditions that have to be met so that errors in data used in analysis pipelines can fail quickly. Similar to 'stopifnot()' but more powerful, friendly, and easier for use in pipelines.
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2024-01-16 |
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r-astsa
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public |
Contains data sets and scripts for analyzing time series in both the frequency and time domains including state space modeling as well as supporting the texts Time Series Analysis and Its Applications: With R Examples (4th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2017, <DOI:10.1007/978-3-319-52452-8>, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, <DOI:10.1201/9780429273285>.
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2024-01-16 |
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r-asyk
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public |
A collection of functions related to density estimation by using Chen's (2000) idea. Mean Squared Errors (MSE) are calculated for estimated curves. For this purpose, R functions allow the distribution to be Gamma, Exponential or Weibull. For details see Chen (2000), Scaillet (2004) <doi:10.1080/10485250310001624819> and Khan and Akbar.
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2024-01-16 |
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r-astrodatr
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public |
A collection of 19 datasets from contemporary astronomical research. They are described the textbook `Modern Statistical Methods for Astronomy with R Applications' by Eric D. Feigelson and G. Jogesh Babu (Cambridge University Press, 2012, Appendix C) or on the website of Penn State's Center for Astrostatistics (http://astrostatistics.psu.edu/datasets). These datasets can be used to exercise methodology involving: density estimation; heteroscedastic measurement errors; contingency tables; two-sample hypothesis tests; spatial point processes; nonlinear regression; mixture models; censoring and truncation; multivariate analysis; classification and clustering; inhomogeneous Poisson processes; periodic and stochastic time series analysis.
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2024-01-16 |
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r-astrofns
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public |
Miscellaneous astronomy functions, utilities, and data.
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2024-01-16 |
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r-assortnet
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public |
Functions to calculate the assortment of vertices in social networks. This can be measured on both weighted and binary networks, with discrete or continuous vertex values.
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2024-01-16 |
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r-ast
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public |
Fits a model to adjust and consider additional variations in three dimensions of age groups, time, and space on residuals excluded from a prediction model that have residual such as: linear regression, mixed model and so on. Details are given in Foreman et al. (2015) <doi:10.1186/1478-7954-10-1>.
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2024-01-16 |
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r-assocind
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public |
Implements several new association indices that can control for various types of errors. Also includes existing association indices and functions for simulating the effects of different rates of error on estimates of association strength between individuals using each method.
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2024-01-16 |
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r-assocafc
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public |
When doing association analysis one does not always have the genotypes for the control population. In such cases it may be necessary to fall back on frequency based tests using well known sources for the frequencies in the control population, for instance, from the 1000 Genomes Project. The Allele Frequency Comparison ('AssocAFC') package performs multiple rare variant association analyses in both population and family-based GWAS (Genome-Wide Association Study) designs. It includes three score tests that are based on the difference of the sum of allele frequencies between cases and controls. Two of these tests, Wcorrected() and Wqls(), are collapsing-based tests and suffer from having protective and risk variants. The third test, afcSKAT(), is a score test that overcomes the mix of SNP (Single-Nucleotide Polymorphism) effect directions. For more details see Saad M and Wijsman EM (2017) <doi:10.1093/bib/bbx107>.
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2024-01-16 |
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r-assertive.reflection
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public |
A set of predicates and assertions for checking the state and capabilities of R, the operating system it is running on, and the IDE being used. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertthat
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None |
An extension to stopifnot() that makes it easy to declare the pre and post conditions that you code should satisfy, while also producing friendly error messages so that your users know what's gone wrong.
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2024-01-16 |
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r-asremlplus
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public |
Assists in automating the selection of terms to include in mixed models when 'asreml' is used to fit the models. Also used to display, in tables and graphs, predictions obtained using any model fitting function and to explore differences between predictions. The content falls into the following natural groupings: (i) Data, (ii) Object manipulation functions, (iii) Model modification functions, (iv) Model testing functions, (v) Model diagnostics functions, (vi) Prediction production and presentation functions, (vii) Response transformation functions, and (viii) Miscellaneous functions (for further details see 'asremlPlus-package' in help). A history of the fitting of a sequence of models is kept in a data frame. Procedures are available for choosing models that conform to the hierarchy or marginality principle and for displaying predictions for significant terms in tables and graphs. The 'asreml' package provides a computationally efficient algorithm for fitting a wide range of linear mixed models using Residual Maximum Likelihood. It is a commercial package that can be purchased from 'VSNi' <https://vsni.co.uk/> as 'asreml-R', who will supply a zip file for local installation/updating (see <https://asreml.kb.vsni.co.uk/>). It is not needed for functions that are methods for 'alldiffs' and 'data.frame' objects. The package 'asremPlus' can also be installed from <http://chris.brien.name/rpackages/>.
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2024-01-16 |
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r-assertive.types
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public |
A set of predicates and assertions for checking the types of variables. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.sets
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public |
A set of predicates and assertions for checking the properties of sets. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.strings
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public |
A set of predicates and assertions for checking the properties of strings. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.properties
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public |
A set of predicates and assertions for checking the properties of variables, such as length, names and attributes. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.numbers
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public |
A set of predicates and assertions for checking the properties of numbers. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.files
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public |
A set of predicates and assertions for checking the properties of files and connections. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.models
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public |
A set of predicates and assertions for checking the properties of models. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.matrices
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public |
A set of predicates and assertions for checking the properties of matrices. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.datetimes
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public |
A set of predicates and assertions for checking the properties of dates and times. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.data.us
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public |
A set of predicates and assertions for checking the properties of US-specific complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.data.uk
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public |
A set of predicates and assertions for checking the properties of UK-specific complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.data
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public |
A set of predicates and assertions for checking the properties of (country independent) complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.code
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public |
A set of predicates and assertions for checking the properties of code. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive.base
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public |
A minimal set of predicates and assertions used by the assertive package. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2024-01-16 |
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r-assertive
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public |
Lots of predicates (is_* functions) to check the state of your variables, and assertions (assert_* functions) to throw errors if they aren't in the right form.
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2024-01-16 |
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r-asht
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public |
Gives some hypothesis test functions (sign test, median and other quantile tests, Wilcoxon signed rank test, coefficient of variation test, test of normal variance, test on weighted sums of Poisson [see Fay and Kim <doi:10.1002/bimj.201600111>], sample size for t-tests with different variances and non-equal n per arm, Behrens-Fisher test, nonparametric ABC intervals, Wilcoxon-Mann-Whitney test [with effect estimates and confidence intervals, see Fay and Malinovsky <doi:10.1002/sim.7890>], two-sample melding tests [see Fay, Proschan, and Brittain <doi:10.1111/biom.12231>], one-way ANOVA allowing var.equal=FALSE [see Brown and Forsythe, 1974, Biometrics]), prevalence confidence intervals that adjust for sensitivity and specificity [see Lang and Reiczigel, 2014 <doi:10.1016/j.prevetmed.2013.09.015>] or Bayer, Fay, and Graubard, 2023 <doi:10.48550/arXiv.2205.13494>). The focus is on hypothesis tests that have compatible confidence intervals, but some functions only have confidence intervals (e.g., prevSeSp).
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2024-01-16 |
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r-ascii
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public |
Coerce R object to 'asciidoc', 'txt2tags', 'restructuredText', 'org', 'textile' or 'pandoc' syntax. Package comes with a set of drivers for 'Sweave'.
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2024-01-16 |
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r-assertable
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public |
Simple, flexible, assertions on data.frame or data.table objects with verbose output for vetting. While other assertion packages apply towards more general use-cases, assertable is tailored towards tabular data. It includes functions to check variable names and values, whether the dataset contains all combinations of a given set of unique identifiers, and whether it is a certain length. In addition, assertable includes utility functions to check the existence of target files and to efficiently import multiple tabular data files into one data.table.
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2024-01-16 |
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r-arulesviz
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public |
Extends package 'arules' with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration. Michael Hahsler (2017) <doi:10.32614/RJ-2017-047>.
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2024-01-16 |
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r-aspi
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public |
Tools for the analysis and visualization of bilateral asymmetry in parasitic infections.
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2024-01-16 |
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r-asnipe
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public |
Implements several tools that are used in animal social network analysis, as described in Whitehead (2007) Analyzing Animal Societies <University of Chicago Press> and Farine & Whitehead (2015) <doi: 10.1111/1365-2656.12418>. In particular, this package provides the tools to infer groups and generate networks from observation data, perform permutation tests on the data, calculate lagged association rates, and performed multiple regression analysis on social network data.
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2024-01-16 |
