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r-smoothmest
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public |
Some M-estimators for 1-dimensional location (Bisquare, ML for the Cauchy distribution, and the estimators from application of the smoothing principle introduced in Hampel, Hennig and Ronchetti (2011) to the above, the Huber M-estimator, and the median, main function is smoothm), and Pitman estimator.
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2023-06-16 |
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r-smoother
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public |
A collection of methods for smoothing numerical data, commencing with a port of the Matlab gaussian window smoothing function. In addition, several functions typically used in smoothing of financial data are included.
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2023-06-16 |
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r-smfilter
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public |
Provides the filtering algorithms for the state space models on the Stiefel manifold as well as the corresponding sampling algorithms for uniform, vector Langevin-Bingham and matrix Langevin-Bingham distributions on the Stiefel manifold.
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2023-06-16 |
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r-smatr
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public |
Methods for fitting bivariate lines in allometry using the major axis (MA) or standardised major axis (SMA), and for making inferences about such lines. The available methods of inference include confidence intervals and one-sample tests for slope and elevation, testing for a common slope or elevation amongst several allometric lines, constructing a confidence interval for a common slope or elevation, and testing for no shift along a common axis, amongst several samples. See Warton et al. 2012 <doi:10.1111/j.2041-210X.2011.00153.x> for methods description.
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2023-06-16 |
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r-simplercache
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public |
Simple result caching in R based on R.cache. The global environment is not considered when caching results simplifying moving files between multiple instances of R. Relies on more base functions than R.cache (e.g. cached results are saved using saveRDS() and readRDS()).
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2023-06-16 |
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r-simdistr
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public |
Assessment of the distributions of baseline continuous and categorical variables in randomised trials. This method is based on the Carlisle-Stouffer method with Monte Carlo simulations. It calculates p-values for each trial baseline variable, as well as combined p-values for each trial - these p-values measure how compatible are distributions of trials baseline variables with random sampling. This package also allows for graphically plotting the cumulative frequencies of computed p-values. Please note that code was partly adapted from Carlisle JB, Loadsman JA. (2017) <doi:10.1111/anae.13650>.
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2023-06-16 |
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r-simcop
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public |
Provides a framework to generating random variates from arbitrary multivariate copulae, while concentrating on (bivariate) extreme value copulae. Particularly useful if the multivariate copulae are not available in closed form.
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2023-06-16 |
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r-sigmanet
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public |
Create interactive graph visualizations using 'Sigma.js' <http://sigmajs.org/>. This package is meant to be used in conjunction with 'igraph', replacing the (somewhat underwhelming) plotting features of the package. The idea is to quickly render graphs, regardless of their size, in a way that allows for easy, iterative modification of aesthetics. Because 'Sigma.js' is a 'javascript' library, the visualizations are inherently interactive and are well suited for integration with 'Shiny' apps. While there are several 'htmlwidgets' focused on network visualization, they tend to underperform on medium to large sized graphs. 'Sigma.js' was designed for larger network visualizations and this package aims to make those strengths available to 'R' users.
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2023-06-16 |
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r-si
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public |
An implementation of four stochastic methods of integrating in R, including: 1. Stochastic Point Method (or Monte Carlo Method); 2. Mean Value Method; 3. Important Sampling Method; 4. Stratified Sampling Method. It can be used to estimate one-dimension or multi-dimension integration by Monte Carlo methods. And the estimated variance (precision) is given. Reference: Caflisch, R. E. (1998) <doi:10.1017/S0962492900002804>.
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2023-06-16 |
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r-shinyglide
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public |
Insert Glide JavaScript component into Shiny applications for carousel or assistant-like user interfaces.
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2023-06-16 |
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r-shapefiles
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public |
Functions to read and write ESRI shapefiles
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2023-06-16 |
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r-sempls
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public |
Fits structural equation models using partial least squares (PLS). The PLS approach is referred to as 'soft-modeling' technique requiring no distributional assumptions on the observed data.
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2023-06-16 |
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r-sdm
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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>.
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2023-06-16 |
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r-scottknott
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public |
Division of an ANOVA experiment treatment means into homogeneous distinct groups using the clustering method of Scott & Knott.
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2023-06-16 |
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r-saves
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public |
The purpose of this package is to be able to save and load only the needed variables/columns of a dataframe in special binary files (tar archives) - which seems to be a lot faster method than loading the whole binary object (RData files) via load() function, or than loading columns from SQLite/MySQL databases via SQL commands (see vignettes). Performance gain on SSD drives is a lot more sensible compared to basic load() function. The performance improvement gained by loading only the chosen variables in binary format can be useful in some special cases (e.g. where merging data tables is not an option and very different datasets are needed for reporting), but be sure if using this package that you really need this, as non-standard file formats are used!
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2023-06-16 |
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r-sautomata
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Machine learning provides algorithms that can learn from data and make inferences or predictions. Stochastic automata is a class of input/output devices which can model components. This work provides implementation an inference algorithm for stochastic automata which is similar to the Viterbi algorithm. Moreover, we specify a learning algorithm using the expectation-maximization technique and provide a more efficient implementation of the Baum-Welch algorithm for stochastic automata. This work is based on Inference and learning in stochastic automata was by Karl-Heinz Zimmermann(2017) <doi:10.12732/ijpam.v115i3.15>.
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2023-06-16 |
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r-sqrl
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public |
Facilitates interaction with ODBC data sources by managing communications on behalf of the user. Supports multi-statement SQL scripts, with or without embedded R.
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2023-06-16 |
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r-spinyreg
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public |
Implements a generative model that uses a spike-and-slab like prior distribution obtained by multiplying a deterministic binary vector. Such a model allows an EM algorithm, optimizing a type-II log-likelihood.
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2023-06-16 |
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r-spiassay
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public |
The SNP Panel Identification Assay (SPIA) is a package that enables an accurate determination of cell line identity from the genotype of single nucleotide polymorphisms (SNPs). The SPIA test allows to discern when two cell lines are close enough to be called similar and when they are not. Details about the method are available at "Demichelis et al. (2008) SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines. Nucleic Acids Res., 3, 2446-2456".
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2023-06-16 |
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r-spi
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public |
Compute the SPI index using R
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2023-06-16 |
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r-spatialcovariance
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public |
Functions that compute the spatial covariance matrix for the matern and power classes of spatial models, for data that arise on rectangular units. This code can also be used for the change of support problem and for spatial data that arise on irregularly shaped regions like counties or zipcodes by laying a fine grid of rectangles and aggregating the integrals in a form of Riemann integration.
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2023-06-16 |
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r-spaa
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public |
Miscellaneous functions for analysing species association and niche overlap.
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2023-06-16 |
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r-source.gist
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public |
Analogous to source(), but works when given a Gist URL or ID.
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2023-06-16 |
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r-soql
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public |
Used to construct the URLs and parameters of 'Socrata Open Data API' <https://dev.socrata.com> calls, using the API's 'SoQL' parameter format. Has method-chained and sensical syntax. Plays well with pipes.
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2023-06-16 |
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r-soniclength
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Estimate the abundance of cell clones from the distribution of lengths of DNA fragments (as created by sonication, whence `sonicLength'). The algorithm in "Estimating abundances of retroviral insertion sites from DNA fragment length data" by Berry CC, Gillet NA, Melamed A, Gormley N, Bangham CR, Bushman FD. Bioinformatics; 2012 Mar 15;28(6):755-62 is implemented. The experimental setting and estimation details are described in detail there. Briefly, integration of new DNA in a host genome (due to retroviral infection or gene therapy) can be tracked using DNA sequencing, potentially allowing characterization of the abundance of individual cell clones bearing distinct integration sites. The locations of integration sites can be determined by fragmenting the host DNA (via sonication or fragmentase), breaking the newly integrated DNA at a known sequence, amplifying the fragments containing both host and integrated DNA, sequencing those amplicons, then mapping the host sequences to positions on the reference genome. The relative number of fragments containing a given position in the host genome estimates the relative abundance of cells hosting the corresponding integration site, but that number is not available and the count of amplicons per fragment varies widely. However, the expected number of distinct fragment lengths is a function of the abundance of cells hosting an integration site at a given position and a certain nuisance parameter. The algorithm implicitly estimates that function to estimate the relative abundance.
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2023-06-16 |
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r-solartime
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Provide utilities to work with solar time, i.e. where noon is exactly when sun culminates. Provides functions for computing sun position and times of sunrise and sunset.
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2023-06-16 |
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r-smvar
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public |
Implements the structural model for variances in order to detect differentially expressed genes from gene expression data
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2023-06-16 |
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r-smithwilsonyieldcurve
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Constructs a yield curve by the Smith-Wilson method from a table of LIBOR and SWAP rates
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2023-06-16 |
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r-smdata
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public |
Contains data files to accompany Smithson & Merkle (2013), Generalized Linear Models for Categorical and Continuous Limited Dependent Variables.
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2023-06-16 |
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r-skywatchr
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public |
Query and download satellite imagery and climate/atmospheric datasets using the SkyWatch API. Search datasets by wavelength (band), cloud cover, resolution, location, date, etc. Get the query results as data frame and as HTML. To learn more about the SkyWatch API, see <https://github.com/skywatchspaceapps/api>.
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2023-06-16 |
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r-skeletor
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public |
A tool for bootstrapping new packages with useful defaults, including a test suite outline that passes checks and helpers for running tests, checking test coverage, building vignettes, and more. Package skeletons it creates are set up for pushing your package to 'GitHub' and using other hosted services for building and test automation.
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2023-06-16 |
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r-simpleneural
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public |
Trains neural networks (multilayer perceptrons with one hidden layer) for bi- or multi-class classification.
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2023-06-16 |
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r-simphe
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public |
Provides functions to simulate single or multiple, independent or correlated phenotype(s) with additive, dominance effects and their interactions. Also includes functions to generate phenotype(s) with specific heritability. Flexible and user-friendly options for simulation.
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2023-06-16 |
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r-shinytree
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public |
Exposes bindings to jsTree -- a JavaScript library that supports interactive trees -- to enable a rich, editable trees in Shiny.
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2023-06-16 |
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r-shinyeffects
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public |
Add fancy CSS effects to your 'shinydashboards' or 'shiny' apps. 100% compatible with 'shinydashboardPlus' and 'bs4Dash'.
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2023-06-16 |
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r-shinyace
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public |
Ace editor bindings to enable a rich text editing environment within Shiny.
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2023-06-16 |
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r-shiftsharese
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public |
Provides confidence intervals in least-squares regressions when the variable of interest has a shift-share structure, and in instrumental variables regressions when the instrument has a shift-share structure. The confidence intervals implement the AKM and AKM0 methods developed in Adão, Kolesár, and Morales (2019) <doi:10.1093/qje/qjz025>.
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2023-06-16 |
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r-shades
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public |
Functions for easily manipulating colours, creating colour scales and calculating colour distances.
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2023-06-16 |
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r-sgrsea
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public |
Provides functions to implement sgRSEA (single-guide RNA Set Enrichment Analysis), which is a robust test for identification of essential genes from genetic screening data using CRISPR (clustered regularly interspaced short palindromic repeats) and Cas9 (CRISPR-associated nuclease 9) system.
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2023-06-16 |
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r-sgee
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public |
Stagewise techniques implemented with Generalized Estimating Equations to handle individual, group, bi-level, and interaction selection. Stagewise approaches start with an empty model and slowly build the model over several iterations, which yields a 'path' of candidate models from which model selection can be performed. This 'slow brewing' approach gives stagewise techniques a unique flexibility that allows simple incorporation of Generalized Estimating Equations; see Vaughan, G., Aseltine, R., Chen, K., Yan, J., (2017) <doi:10.1111/biom.12669> for details.
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2023-06-16 |
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r-settest
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public |
It provides cumulative distribution function (CDF), quantile, p-value, statistical power calculator and random number generator for a collection of group-testing procedures, including the Higher Criticism tests, the one-sided Kolmogorov-Smirnov tests, the one-sided Berk-Jones tests, the one-sided phi-divergence tests, etc. The input are a group of p-values. The null hypothesis is that they are i.i.d. Uniform(0,1). In the context of signal detection, the null hypothesis means no signals. In the context of the goodness-of-fit testing, which contrasts a group of i.i.d. random variables to a given continuous distribution, the input p-values can be obtained by the CDF transformation. The null hypothesis means that these random variables follow the given distribution. For reference, see Hong Zhang, Jiashun Jin and Zheyang Wu. "Distributions and Statistical Power of Optimal Signal-Detection Methods In Finite Cases", submitted.
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2023-06-16 |
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r-sequential
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public |
Functions to calculate exact critical values, statistical power, expected time to signal, and required sample sizes for performing exact sequential analysis. All these calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. In case of group sequential analyses, the group sizes do not have to be specified in advance and the alpha spending can be arbitrarily settled.
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2023-06-16 |
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r-seqrflp
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public |
This package includes functions for handling DNA sequences, especially simulated RFLP and TRFLP pattern based on selected restriction enzyme and DNA sequences.
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2023-06-16 |
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r-seqmon
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public |
S4 class object for creating and managing group sequential designs. It calculates the efficacy and futility boundaries at each look. It allows modifying the design and tracking the design update history.
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2023-06-16 |
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r-separationplot
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public |
Functions to generate separation plots for evaluation of model fit.
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2023-06-16 |
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r-selfingtree
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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.
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2023-06-16 |
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r-searcher
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public |
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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2023-06-16 |
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r-sealasso
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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.
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2023-06-16 |
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r-sdef
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public |
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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2023-06-16 |
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r-scriptexec
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public |
Run complex native scripts with a single command, similar to system commands.
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2023-06-16 |
