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r-sigora
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public |
Pathway Analysis is the process of statistically linking observations on the molecular level to biological processes or pathways on the systems(i.e. organism, organ, tissue, cell) level. Traditionally, pathway analysis methods regard pathways as collections of single genes and treat all genes in a pathway as equally informative. This can lead to identification of spurious pathways as statistically significant, since components are often shared amongst pathways. SIGORA seeks to avoid this pitfall by focusing on genes or gene-pairs that are (as a combination) specific to a single pathway. In relying on such pathway gene-pair signatures (Pathway-GPS), SIGORA inherently uses the status of other genes in the experimental context to identify the most relevant pathways. The current version allows for pathway analysis of human and mouse datasets and contains pre-computed Pathway-GPS data for pathways in the KEGG and Reactome pathway repositories as well as mechanisms for extracting GPS for user supplied repositories.
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2025-04-22 |
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r-sigoptr
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public |
Interfaces with the 'SigOpt' API. More info at <https://sigopt.com>.
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2025-04-22 |
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r-signmedian.test
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public |
Perform sign test on one-sample data, which is one of the oldest non-parametric statistical methods. Assume that X comes from a continuous distribution with median = v ( unknown ). Test the null hypothesis H0: median of X v = mu ( mu is the location parameter and is given in the test ) v.s. the alternative hypothesis H1: v > mu ( or v < mu or v != mu ) and calculate the p-value. When the sample size is large, perform the asymptotic sign test. In both ways, calculate the R-estimate of location of X and the distribution free confidence interval for mu.
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2025-04-22 |
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r-signifreg
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public |
Provide consistent significance controlled variable selection procedure with different directions (forward, backward, stepwise) based on diverse criteria (AIC, BIC, adjusted r-square, and p-value). The algorithm selects a final model with only significant variables based on a correction choice of False Discovery Rate, Bonferroni, or no correction.
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2025-04-22 |
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r-sigmoid
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public |
Several different sigmoid functions are implemented, including a wrapper function, SoftMax preprocessing and inverse functions.
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2025-04-22 |
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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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2025-04-22 |
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r-sightabilitymodel
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public |
Uses logistic regression to model the probability of detection as a function of covariates. This model is then used with observational survey data to estimate population size, while accounting for uncertain detection. See Steinhorst and Samuel (1989).
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2025-04-22 |
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r-sigclust
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public |
SigClust is a statistical method for testing the significance of clustering results. SigClust can be applied to assess the statistical significance of splitting a data set into two clusters. For more than two clusters, SigClust can be used iteratively.
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2025-04-22 |
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r-sig
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public |
Print function signatures and find overly complicated code.
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2025-04-22 |
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r-sievetest
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public |
Functions for making particle-size analysis. Sieve tests are widely used to obtain particle-size distribution of powders or granular materials.
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2025-04-22 |
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r-sieveph
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public |
Implements semiparametric estimation and testing procedures for a continuous, possibly multivariate, mark-specific hazard ratio (treatment/placebo) of an event of interest in a randomized treatment efficacy trial with a time-to-event endpoint, as described in Juraska M and Gilbert PB (2013), Mark-specific hazard ratio model with multivariate continuous marks: an application to vaccine efficacy. Biometrics 69(2):328 337, and in Juraska M and Gilbert PB (2015), Mark-specific hazard ratio model with missing multivariate marks. Lifetime Data Analysis 22(4): 606-25. The former considers continuous multivariate marks fully observed in all subjects who experience the event of interest, whereas the latter extends the previous work to allow multivariate marks that are subject to missingness-at-random. For models with missing marks, two estimators are implemented based on (i) inverse probability weighting (IPW) of complete cases, and (ii) augmentation of the IPW estimating functions by leveraging correlations between the mark and auxiliary data to 'impute' the expected profile score vectors for subjects with missing marks. The augmented IPW estimator is doubly robust and recommended for use with incomplete mark data. The methods make two key assumptions: (i) the time-to-event is assumed to be conditionally independent of the mark given treatment, and (ii) the weight function in the semiparametric density ratio/biased sampling model is assumed to be exponential. Diagnostic testing procedures for evaluating validity of both assumptions are implemented. Summary and plotting functions are provided for estimation and inferential results.
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2025-04-22 |
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r-sier
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public |
Methods for regression with high-dimensional predictors and univariate or maltivariate response variables. It considers the decomposition of the coefficient matrix that leads to the best approximation to the signal part in the response given any rank, and estimates the decomposition by solving a penalized generalized eigenvalue problem followed by a least squares procedure. Ruiyan Luo and Xin Qi (2017) <doi:10.1016/j.jmva.2016.09.005>.
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2025-04-22 |
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r-siebanxicor
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public |
Allows to retrieve time series of all indicators available in the Bank of Mexico's Economic Information System (<http://www.banxico.org.mx/SieInternet/>).
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2025-04-22 |
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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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2025-04-22 |
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r-shutterstock
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public |
Access 'Shutterstock' API from R. The 'Shutterstock' API presents access to search, view, license and download the media and information from the 'Shutterstock's library <https://api-reference.shutterstock.com/>.
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2025-04-22 |
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r-shuffle
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public |
Implementation of the shuffle estimator, a non-parametric estimator for signal and noise variance under mild noise correlations.
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2025-04-22 |
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r-showimage
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public |
Sometimes it is handy to be able to view an image file on an 'R' graphics device. This package just does that. Currently it supports 'PNG' files.
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2025-04-22 |
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r-shotgroups
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public |
Analyzes shooting data with respect to group shape, precision, and accuracy. This includes graphical methods, descriptive statistics, and inference tests using standard, but also non-parametric and robust statistical methods. Implements distributions for radial error in bivariate normal variables. Works with files exported by 'OnTarget PC/TDS', 'Silver Mountain' e-target, 'ShotMarker' e-target, or 'Taran', as well as with custom data files in text format. Supports inference from range statistics like extreme spread. Includes a set of web-based graphical user interfaces.
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2025-04-22 |
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r-shopifyr
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public |
An interface to the Admin API of the E-commerce service Shopify, (<https://help.shopify.com/en/api/reference>).
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2025-04-22 |
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r-shipunov
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public |
A collection of functions for data manipulation, plotting and statistical computing, to use separately or with the book "Visual Statistics. Use R!": Shipunov (2019) <http://ashipunov.info/shipunov/software/r/r-en.htm>. Most useful functions are probably Bclust(), Jclust() and BootA() which bootstrap hierarchical clustering; Recode...() which multiple recode in a fast, flexible and simple way; Misclass() which outputs confusion matrix even if classes are not concerted; Overlap() which calculates overlaps of convex hulls from any projection; and Pleiad() which is fast and flexible correlogram. In fact, there are much more useful functions, please see documentation.
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2025-04-22 |
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r-ship
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public |
The SHIP-package allows the estimation of various types of shrinkage covariance matrices. These types differ in terms of the so-called covariance target (to be chosen by the user), the highly structured matrix which the standard unbiased sample covariance matrix is shrunken towards and which optionally incorporates prior biological knowledge extracted from the database KEGG. The shrinkage intensity is obtained via an analytical procedure.
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2025-04-22 |
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r-shinywidgets
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public |
Collection of custom input controls and user interface components for 'Shiny' applications. Give your applications a unique and colorful style !
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2025-04-22 |
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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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2025-04-22 |
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r-shinytoastr
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public |
Browser notifications in 'Shiny' apps, using 'toastr': <https://github.com/CodeSeven/toastr#readme>.
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2025-04-22 |
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r-shinytime
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public |
Provides a time input widget for Shiny. This widget allows intuitive time input in the '[hh]:[mm]:[ss]' or '[hh]:[mm]' (24H) format by using a separate numeric input for each time component. The interface with R uses date-time objects. See the project page for more information and examples.
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2025-04-22 |
