|
r-sendmailr
|
public |
Package contains a simple SMTP client with minimal dependencies which provides a portable solution for sending email, including file attachments and inline html reports, from within R. SMTP Authentication and SSL/STARTTLS is implemented using curl.
|
2024-01-16 |
|
r-semeff
|
public |
Automatically calculate direct, indirect, and total effects for piecewise structural equation models, comprising lists of fitted models representing structured equations (Lefcheck, 2016 <doi:10/f8s8rb>). Confidence intervals are provided via bootstrapping.
|
2024-01-16 |
|
r-semtools
|
public |
Provides tools for structural equation modeling, many of which extend the 'lavaan' package; for example, to pool results from multiple imputations, probe latent interactions, or test measurement invariance.
|
2024-01-16 |
|
r-seewave
|
public |
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>.
|
2024-01-16 |
|
r-semnetdictionaries
|
public |
Implements dictionaries that can be used in the 'SemNetCleaner' package. Also includes several functions aimed at facilitating the text cleaning analysis in the 'SemNetCleaner' package. This package is designed to integrate and update word lists and dictionaries based on each user's individual needs by allowing users to store and save their own dictionaries. Dictionaries can be added to the 'SemNetDictionaries' package by submitting user-defined dictionaries to <https://github.com/AlexChristensen/SemNetDictionaries>.
|
2024-01-16 |
|
r-semipar
|
public |
Functions for semiparametric regression analysis, to complement the book: Ruppert, D., Wand, M.P. and Carroll, R.J. (2003). Semiparametric Regression. Cambridge University Press.
|
2024-01-16 |
|
r-seminr
|
public |
A powerful, easy to syntax for specifying and estimating complex Structural Equation Models. Models can be estimated using Partial Least Squares Path Modeling or Covariance-Based Structural Equation Modeling or covariance based Confirmatory Factor Analysis. Methods described in Ray, Danks, and Valdez (2021).
|
2024-01-16 |
|
r-semid
|
public |
Provides routines to check identifiability or non-identifiability of linear structural equation models as described in Drton, Foygel, and Sullivant (2011) <doi:10.1214/10-AOS859>, Foygel, Draisma, and Drton (2012) <doi:10.1214/12-AOS1012>, and other works. The routines are based on the graphical representation of structural equation models.
|
2024-01-16 |
|
r-selfingtree
|
public |
A probability tree allows to compute probabilities of complex events, such as genotype probabilities in intermediate generations of inbreeding through recurrent self-fertilization (selfing). This package implements functionality to compute probability trees for two- and three-marker genotypes in the F2 to F7 selfing generations. The conditional probabilities are derived automatically and in symbolic form. The package also provides functionality to extract and evaluate the relevant probabilities.
|
2024-01-16 |
|
r-seleniumpipes
|
public |
The W3C WebDriver specification defines a way for out-of-process programs to remotely instruct the behaviour of web browsers. It is detailed at <https://w3c.github.io/webdriver/webdriver-spec.html>. This package provides an R client implementing the W3C specification.
|
2024-01-16 |
|
r-selemix
|
public |
Detection of outliers and influential errors using a latent variable model.
|
2024-01-16 |
|
r-selectiongain
|
public |
Multi-stage selection is practiced in numerous fields of life and social sciences and particularly in breeding. A special characteristic of multi-stage selection is that candidates are evaluated in successive stages with increasing intensity and effort, and only a fraction of the superior candidates is selected and promoted to the next stage. For the optimum design of such selection programs, the selection gain plays a crucial role. It can be calculated by integration of a truncated multivariate normal (MVN) distribution. While mathematical formulas for calculating the selection gain and the variance among selected candidates were developed long time ago, solutions for numerical calculation were not available. This package can also be used for optimizing multi-stage selection programs for a given total budget and different costs of evaluating the candidates in each stage.
|
2024-01-16 |
|
r-selectr
|
public |
Translates a CSS3 selector into an equivalent XPath expression. This allows us to use CSS selectors when working with the XML package as it can only evaluate XPath expressions. Also provided are convenience functions useful for using CSS selectors on XML nodes. This package is a port of the Python package 'cssselect' (<https://cssselect.readthedocs.io/>).
|
2024-01-16 |
|
r-selectmeta
|
public |
Publication bias, the fact that studies identified for inclusion in a meta analysis do not represent all studies on the topic of interest, is commonly recognized as a threat to the validity of the results of a meta analysis. One way to explicitly model publication bias is via selection models or weighted probability distributions. In this package we provide implementations of several parametric and nonparametric weight functions. The novelty in Rufibach (2011) is the proposal of a non-increasing variant of the nonparametric weight function of Dear & Begg (1992). The new approach potentially offers more insight in the selection process than other methods, but is more flexible than parametric approaches. To maximize the log-likelihood function proposed by Dear & Begg (1992) under a monotonicity constraint we use a differential evolution algorithm proposed by Ardia et al (2010a, b) and implemented in Mullen et al (2009). In addition, we offer a method to compute a confidence interval for the overall effect size theta, adjusted for selection bias as well as a function that computes the simulation-based p-value to assess the null hypothesis of no selection as described in Rufibach (2011, Section 6).
|
2024-01-16 |
|
r-sejong
|
public |
Sejong(http://www.sejong.or.kr/) corpus and Hannanum(http://semanticweb.kaist.ac.kr/home/index.php/HanNanum) dictionaries for KoNLP
|
2024-01-16 |
|
r-selectapref
|
public |
Provides indices such as Manly's alpha, foraging ratio, and Ivlev's selectivity to allow for analysis of dietary selectivity and preference. Can accommodate multiple experimental designs such as constant prey number of prey depletion. Please contact the package maintainer with any publications making use of this package in an effort to maintain a repository of dietary selections studies.
|
2024-01-16 |
|
r-see
|
public |
Provides plotting utilities supporting packages in the 'easystats' ecosystem (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://materialui.co/colors>. References: Lüdecke et al. (2021) <doi:10.21105/joss.03393>.
|
2024-01-16 |
|
r-seastests
|
public |
An overall test for seasonality of a given time series in addition to a set of individual seasonality tests as described by Ollech and Webel (forthcoming): An overall seasonality test. Bundesbank Discussion Paper.
|
2024-01-16 |
|
r-seismic
|
public |
An implementation of self-exciting point process model for information cascades, which occurs when many people engage in the same acts after observing the actions of others (e.g. post resharings on Facebook or Twitter). It provides functions to estimate the infectiousness of an information cascade and predict its popularity given the observed history. See <http://snap.stanford.edu/seismic/> for more information and datasets.
|
2024-01-16 |
|
r-segmented
|
public |
Given a regression model, segmented `updates' it by adding one or more segmented (i.e., piece-wise linear) relationships. Several variables with multiple breakpoints are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>). Segmented mixed models, i.e. random effects in the change point, are discussed in in Muggeo (2014, <doi:10.1177/1471082X13504721>).
|
2024-01-16 |
|
r-seasonalview
|
public |
A graphical user interface to the 'seasonal' package and 'X-13ARIMA-SEATS', the U.S. Census Bureau's seasonal adjustment software. Unifies the code base of <http://www.seasonal.website> and the GUI in the 'seasonal' package.
|
2024-01-16 |
|
r-seedcalc
|
public |
Functions to calculate seed germination and seedling emergence and growth indexes. The main indexes for germination and seedling emergence, considering the time for seed germinate are: T10, T50 and T90, in Farooq et al. (2005) <10.1111/j.1744-7909.2005.00031.x>; and MGT, in Labouriau (1983). Considering the germination speed are: Germination Speed Index, in Maguire (1962), Mean Germination Rate, in Labouriau (1983); considering the homogeneity of germination are: Coefficient of Variation of the Germination Time, in Carvalho et al. (2005) <10.1590/S0100-84042005000300018>, and Variance of Germination, in Labouriau (1983); Uncertainty, in Labouriau and Valadares (1976) <ISSN:0001-3765>; and Synchrony, in Primack (1980). The main seedling indexes are Growth, in Sako (2001), Uniformity, in Sako (2001) and Castan et al. (2018) <doi:10.1590/1678-992x-2016-0401>; and Vigour, in Medeiros and Pereira (2018) <doi:10.1590/1983-40632018v4852340>.
|
2024-01-16 |
|
r-seeclickfixr
|
public |
Provides a wrapper to access data from the SeeClickFix web API for R. SeeClickFix is a central platform employed by many cities that allows citizens to request their city's services. This package creates several functions to work with all the built-in calls to the SeeClickFix API. Allows users to download service request data from numerous locations in easy-to-use dataframe format manipulable in standard R functions.
|
2024-01-16 |
|
r-sdprior
|
public |
Utility functions for scale-dependent and alternative hyperpriors. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. Hyperpriors for all effects can be elicitated within the package. Including complex tensor product interaction terms and variable selection priors. The basic model is explained in in Klein and Kneib (2016) <doi:10.1214/15-BA983>.
|
2024-01-16 |
|
r-secret
|
public |
Allow sharing sensitive information, for example passwords, 'API' keys, etc., in R packages, using public key cryptography.
|
2024-01-16 |
|
r-seasonal
|
public |
Easy-to-use interface to X-13-ARIMA-SEATS, the seasonal adjustment software by the US Census Bureau. It offers full access to almost all options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model search, outlier detection and support for user defined holiday variables, such as Chinese New Year or Indian Diwali. A graphical user interface can be used through the 'seasonalview' package. Uses the X-13-binaries from the 'x13binary' package.
|
2024-01-16 |
|
r-searcher
|
public |
Provides a search interface to look up terms on 'Google', 'Bing', 'DuckDuckGo', 'Startpage', 'Ecosia', 'rseek', 'Twitter', 'StackOverflow', 'RStudio Community', 'GitHub', and 'BitBucket'. Upon searching, a browser window will open with the aforementioned search results.
|
2024-01-16 |
|
r-seacarb
|
public |
Calculates parameters of the seawater carbonate system and assists the design of ocean acidification perturbation experiments.
|
2024-01-16 |
|
r-sda
|
public |
Provides an efficient framework for high-dimensional linear and diagonal discriminant analysis with variable selection. The classifier is trained using James-Stein-type shrinkage estimators and predictor variables are ranked using correlation-adjusted t-scores (CAT scores). Variable selection error is controlled using false non-discovery rates or higher criticism.
|
2024-01-16 |
|
r-sealasso
|
public |
Standard error adjusted adaptive lasso (SEA-lasso) is a version of the adaptive lasso, which incorporates OLS standard error to the L1 penalty weight. This method is intended for variable selection under linear regression settings (n > p). This new weight assignment strategy is especially useful when the collinearity of the design matrix is a concern.
|
2024-01-16 |
|
r-sdt
|
public |
Functions for self-determination motivation theory (SDT) to compute measures of motivation internalization, motivation simplex structure, and of the original and adjusted self-determination or relative autonomy index. SDT was introduced by Deci and Ryan (1985) <doi:10.1007/978-1-4899-2271-7>. See package?SDT for an overview.
|
2024-01-16 |
|
r-sdmpredictors
|
public |
Terrestrial and marine predictors for species distribution modelling from multiple sources, including WorldClim <https://www.worldclim.org/>,, ENVIREM <https://envirem.github.io/>, Bio-ORACLE <https://bio-oracle.org/> and MARSPEC <http://www.marspec.org/>.
|
2024-01-16 |
|
r-sdamr
|
public |
Data sets and functions to support the books "Statistics: Data analysis and modelling" by Speekenbrink, M. (2021) <https://mspeekenbrink.github.io/sdam-book/> and "An R companion to Statistics: data analysis and modelling" by Speekenbrink, M. (2021) <https://mspeekenbrink.github.io/sdam-r-companion/>. All datasets analysed in these books are provided in this package. In addition, the package provides functions to compute sample statistics (variance, standard deviation, mode), create raincloud and enhanced Q-Q plots, and expand Anova results into omnibus tests and tests of individual contrasts.
|
2024-01-16 |
|
r-sdmvspecies
|
public |
A software package help user to create virtual species for species distribution modelling. It includes several methods to help user to create virtual species distribution map. Those maps can be used for Species Distribution Modelling (SDM) study. SDM use environmental data for sites of occurrence of a species to predict all the sites where the environmental conditions are suitable for the species to persist, and may be expected to occur.
|
2024-01-16 |
|
r-sdm
|
public |
An extensible framework for developing species distribution models using individual and community-based approaches, generate ensembles of models, evaluate the models, and predict species potential distributions in space and time. For more information, please check the following paper: Naimi, B., Araujo, M.B. (2016) <doi:10.1111/ecog.01881>.
|
2024-01-16 |
|
r-scpubr
|
public |
A system that provides a streamlined way of generating publication ready plots for known Single-Cell transcriptomics data in a “publication ready” format. This is, the goal is to automatically generate plots with the highest quality possible, that can be used right away or with minimal modifications for a research article.
|
2024-01-16 |
|
r-sdcspatial
|
public |
Privacy protected raster maps can be created from spatial point data. Protection methods include smoothing of dichotomous variables by de Jonge and de Wolf (2016) <doi:10.1007/978-3-319-45381-1_9>, continuous variables by de Wolf and de Jonge (2018) <doi:10.1007/978-3-319-99771-1_23>, suppressing revealing values and a generalization of the quad tree method by Suñé, Rovira, Ibáñez and Farré (2017) <doi:10.2901/EUROSTAT.C2017.001>.
|
2024-01-16 |
|
r-sdaa
|
public |
Functions and Datasets from Lohr, S. (1999), Sampling: Design and Analysis, Duxbury.
|
2024-01-16 |
|
r-scoringutils
|
public |
Provides a collection of metrics and proper scoring rules (Tilmann Gneiting & Adrian E Raftery (2007) <doi:10.1198/016214506000001437>, Jordan, A., Krüger, F., & Lerch, S. (2019) <doi:10.18637/jss.v090.i12>) within a consistent framework for evaluation, comparison and visualisation of forecasts. In addition to proper scoring rules, functions are provided to assess bias, sharpness and calibration (Sebastian Funk, Anton Camacho, Adam J. Kucharski, Rachel Lowe, Rosalind M. Eggo, W. John Edmunds (2019) <doi:10.1371/journal.pcbi.1006785>) of forecasts. Several types of predictions (e.g. binary, discrete, continuous) which may come in different formats (e.g. forecasts represented by predictive samples or by quantiles of the predictive distribution) can be evaluated. Scoring metrics can be used either through a convenient data.frame format, or can be applied as individual functions in a vector / matrix format. All functionality has been implemented with a focus on performance and is robustly tested.
|
2024-01-16 |
|
r-scrobbler
|
public |
'Last.fm'<https://www.last.fm> is a music platform focussed on building a detailed profile of a users listening habits. It does this by 'scrobbling' (recording) every track you listen to on other platforms ('spotify', 'youtube', 'soundcloud' etc) and transferring them to your 'Last.fm' database. This allows 'Last.fm' to act as a complete record of your entire listening history. 'scrobbler' provides helper functions to download and analyse your listening history in R.
|
2024-01-16 |
|
r-scrt
|
public |
Design single-case phase, alternation and multiple-baseline experiments, and conduct randomization tests on data gathered by means of such designs, as discussed in Bulte and Onghena (2013) <doi:10.22237/jmasm/1383280020>.
|
2024-01-16 |
|
r-scorecard
|
public |
The `scorecard` package makes the development of credit risk scorecard easier and efficient by providing functions for some common tasks, such as data partition, variable selection, woe binning, scorecard scaling, performance evaluation and report generation. These functions can also used in the development of machine learning models. The references including: 1. Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: Development and Implementation Using SAS. 2. Siddiqi, N. (2006, ISBN: 9780471754510). Credit risk scorecards. Developing and Implementing Intelligent Credit Scoring.
|
2024-01-16 |
|
r-scripturs
|
public |
Full text, in data frames containing one row per verse, of the Standard Works of The Church of Jesus Christ of Latter-day Saints (LDS). These are the Old Testament, (KJV), the New Testament (KJV), the Book of Mormon, the Doctrine and Covenants, and the Pearl of Great Price.
|
2024-01-16 |
|
r-scriptname
|
public |
A small set of functions wrapping up the call stack and command line inspection needed to determine a running script's filename from within the script itself.
|
2024-01-16 |
|
r-scriptexec
|
public |
Run complex native scripts with a single command, similar to system commands.
|
2024-01-16 |
|
r-scrime
|
public |
Tools for the analysis of high-dimensional data developed/implemented at the group "Statistical Complexity Reduction In Molecular Epidemiology" (SCRIME). Main focus is on SNP data. But most of the functions can also be applied to other types of categorical data.
|
2024-01-16 |
|
r-screenclean
|
public |
Routines for a collection of screen-and-clean type variable selection procedures, including UPS and GS.
|
2024-01-16 |
|
r-scraep
|
public |
Tools for scraping information from webpages and other XML contents, using XPath or CSS selectors.
|
2024-01-16 |
|
r-scperf
|
public |
Implements different inventory models, the bullwhip effect and other supply chain performance variables. Marchena Marlene (2010) <arXiv:1009.3977>.
|
2024-01-16 |
|
r-scottknott
|
public |
Perform the balanced (Scott and Knott, 1974) and unbalanced <doi:10.1590/1984-70332017v17n1a1> Scott & Knott algorithm.
|
2024-01-16 |
