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r-seasonal
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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.
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2025-03-25 |
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r-seasic
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This package conducts Score Equity Assessment (SEA; Dorans, 2004) by calculating and plotting multiple SEA indices as introduced by a variety of authors and summarized by Huggins and Penfield (2012).
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2025-03-25 |
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r-searcher
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Provides a search interface to look up terms on 'Google', 'Bing', 'DuckDuckGo', 'Startpage', 'StackOverflow', 'RStudio Community', 'GitHub', and 'BitBucket'. Upon searching, a browser window will open with the aforementioned search results.
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2025-03-25 |
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r-searchable
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Provides functionality for searching / subsetting and slicing named objects using 'stringr/i'-style modifiers by case (in)sensitivity, regular expressions or fixed expressions; searches uses the standard '[' operator and allows specification of default search behavior to either the search target (named object) and/or the search pattern.
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2025-03-25 |
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r-sealasso
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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.
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2025-03-25 |
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r-sdtoolkit
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Implements algorithms to help with scenario discovery - currently only modified version of the the Patient Rule Induction Method.
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2025-03-25 |
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r-sdt
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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.
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2025-03-25 |
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r-sdmvspecies
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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.
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2025-03-25 |
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r-sdm
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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>.
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2025-03-25 |
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r-sdef
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Performs two tests to evaluate if the experiments are associated and returns a list of interesting features common to all the experiments.
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2025-03-25 |
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r-sddpack
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The semidiscrete decomposition (SDD) approximates a matrix as a weighted sum of outer products formed by vectors with entries constrained to be in the set {-1, 0, 1}.
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2025-03-25 |
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r-sdcspatial
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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>.
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2025-03-25 |
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r-sdaa
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public |
Functions and Datasets from Lohr, S. (1999), Sampling: Design and Analysis, Duxbury.
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2025-03-25 |
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r-scrt
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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>.
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2025-03-25 |
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r-scrselect
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Contains four functions used in the DIC-tau_g procedure. SCRSELECT() and SCRSELECTRUN() uses Stochastic Search Variable Selection to select important covariates in the three hazard functions of a semi-competing risks model. These functions perform the Gibbs sampler for variable selection and a Metropolis-Hastings-Green sampler for the number of split points and parameters for the three baseline hazard function. The function SCRSELECT() returns the posterior sample of all quantities sampled in the Gibbs sampler after a burn-in period to a desired file location, while the function SCRSELECTRUN() returns posterior values of important quantities to the DIC-Tau_g procedure in a list. The function DICTAUG() returns a list containing the DIC values for the unique models visited by the DIC-Tau_g grid search. The function ReturnModel() uses SCRSELECTRUN() and DICTAUG() to return a summary of the posterior coefficient vectors for the optimal model along with saving this posterior sample to a desired path location.
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2025-03-25 |
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r-scrobbler
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'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.
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2025-03-25 |
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r-scripturs
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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.
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2025-03-25 |
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r-scriptname
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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.
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2025-03-25 |
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r-scriptexec
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Run complex native scripts with a single command, similar to system commands.
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2025-03-25 |
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r-scriptests
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Support for using .Rt (transcript) tests in the tests directory of a package. Provides more convenience and features than the standard .R/.Rout.save tests. Tests can be run under R CMD check and also interactively. Provides source.pkg() for quickly loading code, DLLs, and data from a package for use in an edit/compile/test development cycle.
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2025-03-25 |
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r-scrime
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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.
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2025-03-25 |
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r-screenclean
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Routines for a collection of screen-and-clean type variable selection procedures, including UPS and GS.
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2025-03-25 |
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r-scraper
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public |
Tools for Scraping Data from Web-Based Documents
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2025-03-25 |
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r-scraep
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public |
A utility to webscrape the in-house careers of members of the European parliament, from its website <http://www.europarl.europa.eu>.
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2025-03-25 |
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r-scrabblescore
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Given a word will produce that word's scrabble score. Unlike many naive implementations this package takes into consideration the distribution of letter in scrabble. So a word like 'zzz' will be scored '10' rather than '30'.
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2025-03-25 |
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r-scperf
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Implements different inventory models, the bullwhip effect and other supply chain performance variables. Marchena Marlene (2010) <arXiv:1009.3977>.
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2025-03-25 |
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r-scottknott
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Division of an ANOVA experiment treatment means into homogeneous distinct groups using the clustering method of Scott & Knott.
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2025-03-25 |
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r-scoring
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Evaluating probabilistic forecasts via proper scoring rules. scoring implements the beta, power, and pseudospherical families of proper scoring rules, along with ordered versions of the latter two families. Included among these families are popular rules like the Brier (quadratic) score, logarithmic score, and spherical score. For two-alternative forecasts, also includes functionality for plotting scores that one would obtain under specific scoring rules.
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2025-03-25 |
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r-scorer2
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This package contains the functions necessary to run the SCORER 2.0 algorithm. SCORER 2.0 can be used to differentiate between parallel dimeric and trimeric coiled-coil sequence, which are the two most more frequent coiled-coil structures observed naturally. As such, SCORER 2.0 is particularly useful for researchers looking to characterize novel coiled-coil sequences. It may also be used to assist in the structural characterization of synthetic coiled-coil sequences. Also included in this package are functions that allows the user to retrain the SCORER 2.0 algorithm using user-defined training data.
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2025-03-25 |
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r-scoreggum
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Estimate GGUM Person Parameters Using Pre-Calibrated Item Parameters and Binary or Graded Disagree-Agree Responses
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2025-03-25 |
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r-scma
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Perform meta-analysis of single-case experiments, including calculating various effect size measures (SMD, PND, PEM and NAP) and probability combining (additive and multiplicative method), as discussed in Bulte and Onghena (2013) <doi:10.22237/jmasm/1383280020>.
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2025-03-25 |
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r-sciviews
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Functions to install SciViews additions to R, and more tools.
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2025-03-25 |
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r-sciplot
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A collection of functions that creates graphs with error bars for data collected from one-way or higher factorial designs.
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2025-03-25 |
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r-scina
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An automatic cell type detection and assignment algorithm for single cell RNA-Seq and Cytof/FACS data. 'SCINA' is capable of assigning cell type identities to a pool of cells profiled by scRNA-Seq or Cytof/FACS data with prior knowledge of markers, such as genes and protein symbols that are highly or lowly expressed in each category. See Zhang Z, et al (2019) <doi:10.3390/genes10070531> for more details.
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2025-03-25 |
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r-scifigure
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Users may specify what fundamental qualities of a new study have or have not changed in an attempt to reproduce or replicate an original study. A comparison of the differences is visualized. Visualization approach follows 'Patil', 'Peng', and 'Leek' (2016) <doi:10.1101/066803>.
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2025-03-25 |
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r-scientotext
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It involves bibliometric indicators calculation from bibliometric data.It also deals pattern analysis using the text part of bibliometric data.The bibliometric data are obtained from mainly Web of Science and Scopus.
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2025-03-25 |
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r-scico
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Colour choice in information visualisation is important in order to avoid being mislead by inherent bias in the used colour palette. The 'scico' package provides access to the perceptually uniform and colour-blindness friendly palettes developed by Fabio Crameri and released under the "Scientific Colour-Maps" moniker. The package contains 24 different palettes and includes both diverging and sequential types.
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2025-03-25 |
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r-schumaker
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This is a shape preserving spline <doi:10.1137/0720057> which is guaranteed to be monotonic and concave or convex if the data is monotonic and concave or convex. It does not use any optimisation and is therefore quick and smoothly converges to a fixed point in economic dynamics problems including value function iteration. It also automatically gives the first two derivatives of the spline and options for determining behaviour when evaluated outside the interpolation domain.
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2025-03-25 |
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r-schorsch
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Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg. For details on the implemented methods, see Roland Pfister and Markus Janczyk (2016) <doi: 10.20982/tqmp.12.2.p147>.
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2025-03-25 |
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r-schoolmath
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This package contains functions and datasets for math taught in school. A main focus is set to prime-calculation
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2025-03-25 |
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r-schoenberg
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Functions for creating and manipulating 12-tone (i.e., dodecaphonic) musical matrices using Arnold Schoenberg's (1923) serialism technique. This package can generate random 12-tone matrices and can generate matrices using a pre-determined sequence of notes.
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2025-03-25 |
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r-scenario
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Uses the neural gas algorithm to construct a scenario tree for use in multi-stage stochastic programming. The primary input is a set of initial scenarios or realizations of a disturbance. The scenario tree nodal structure must be predefined using a scenario tree nodal partition matrix.
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2025-03-25 |
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r-scdhlm
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Provides a set of tools for estimating hierarchical linear models and effect sizes based on data from single-case designs. Functions are provided for calculating standardized mean difference effect sizes that are directly comparable to standardized mean differences estimated from between-subjects randomized experiments, as described in Hedges, Pustejovsky, and Shadish (2012) <DOI:10.1002/jrsm.1052>; Hedges, Pustejovsky, and Shadish (2013) <DOI:10.1002/jrsm.1086>; and Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>. Includes an interactive web interface.
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2025-03-25 |
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r-scdensity
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Implements methods for obtaining kernel density estimates subject to a variety of shape constraints (unimodality, bimodality, symmetry, tail monotonicity, bounds, and constraints on the number of inflection points). Enforcing constraints can eliminate unwanted waves or kinks in the estimate, which improves its subjective appearance and can also improve statistical performance. The main function scdensity() is very similar to the density() function in 'stats', allowing shape-restricted estimates to be obtained with little effort. The methods implemented in this package are described in Wolters and Braun (2017) <doi:10.1080/03610918.2017.1288247>, Wolters (2012) <doi:10.18637/jss.v047.i06>, and Hall and Huang (2002) <http://www3.stat.sinica.edu.tw/statistica/j12n4/j12n41/j12n41.htm>. See the scdensity() help for for full citations.
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2025-03-25 |
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r-scbmeanfd
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Statistical methods for estimating and inferring the mean of functional data. The methods include simultaneous confidence bands, local polynomial fitting, bandwidth selection by plug-in and cross-validation, goodness-of-fit tests for parametric models, equality tests for two-sample problems, and plotting functions.
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2025-03-25 |
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r-scatterplot3d
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Plots a three dimensional (3D) point cloud.
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2025-03-25 |
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r-scatterd3
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Creates 'D3' 'JavaScript' scatterplots from 'R' with interactive features : panning, zooming, tooltips, etc.
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2025-03-25 |
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r-scam
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Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor (Pya and Wood, 2015) <doi:10.1007/s11222-013-9448-7>. Models can contain multiple shape constrained (univariate and/or bivariate) and unconstrained terms. The routines of gam() in package 'mgcv' are used for setting up the model matrix, printing and plotting the results. Penalized likelihood maximization based on Newton-Raphson method is used to fit a model with multiple smoothing parameter selection by GCV or UBRE/AIC.
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2025-03-25 |
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r-scalreg
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Algorithms for fitting scaled sparse linear regression and estimating precision matrices.
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2025-03-25 |
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r-scagnostics
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Calculates graph theoretic scagnostics. Scagnostics describe various measures of interest for pairs of variables, based on their appearance on a scatterplot. They are useful tool for discovering interesting or unusual scatterplots from a scatterplot matrix, without having to look at every individual plot.
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2025-03-25 |
