Found 1144 packages in 0.45 seconds
Safe, Multiple, Simultaneous String Substitution
Designed to enable simultaneous substitution in strings in a safe fashion. Safe means it does not rely on placeholders (which can cause errors in same length matches).
Cross-Validated Area Under the ROC Curve Confidence Intervals
Tools for working with and evaluating cross-validated area under the ROC curve (AUC) estimators. The primary functions of the package are ci.cvAUC and ci.pooled.cvAUC, which report cross-validated AUC and compute confidence intervals for cross-validated AUC estimates based on influence curves for i.i.d. and pooled repeated measures data, respectively. One benefit to using influence curve based confidence intervals is that they require much less computation time than bootstrapping methods. The utility functions, AUC and cvAUC, are simple wrappers for functions from the ROCR package.
An Ensemble Method for Combining Subset-Specific Algorithm Fits
The Subsemble algorithm is a general subset ensemble prediction method, which can be used for small, moderate, or large datasets. Subsemble partitions the full dataset into subsets of observations, fits a specified underlying algorithm on each subset, and uses a unique form of k-fold cross-validation to output a prediction function that combines the subset-specific fits. An oracle result provides a theoretical performance guarantee for Subsemble. The paper, "Subsemble: An ensemble method for combining subset-specific algorithm fits" is authored by Stephanie Sapp, Mark J. van der Laan & John Canny (2014)
Classes for Relational Data
Tools to create and modify network objects. The network class can represent a range of relational data types, and supports arbitrary vertex/edge/graph attributes.
Using CF-Compliant Calendars with Climate Projection Data
Support for all calendars as specified in the Climate and Forecast (CF) Metadata Conventions for climate and forecasting data. The CF Metadata Conventions is widely used for distributing files with climate observations or projections, including the Coupled Model Intercomparison Project (CMIP) data used by climate change scientists and the Intergovernmental Panel on Climate Change (IPCC). This package specifically allows the user to work with any of the CF-compliant calendars (many of which are not compliant with POSIXt). The CF time coordinate is formally defined in the CF Metadata Conventions document available at < https://cf-convention.github.io/Data/cf-conventions/cf-conventions-1.13/cf-conventions.html#time-coordinate>.
Analyzing Data with Cellwise Outliers
Tools for detecting cellwise outliers and robust methods to analyze
data which may contain them. Contains the implementation of the algorithms described in
Rousseeuw and Van den Bossche (2018)
Easily Work with 'Bootstrap' Icons
Easily use 'Bootstrap' icons inside 'Shiny' apps and 'R Markdown' documents. More generally, icons can be inserted in any 'htmltools' document through inline 'SVG'.
Network Meta-Analysis Using Bayesian Methods
Network meta-analyses (mixed treatment comparisons) in the Bayesian
framework using JAGS. Includes methods to assess heterogeneity and
inconsistency, and a number of standard visualizations.
van Valkenhoef et al. (2012)
Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', ...
Reading and writing data stored by some versions of 'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', and for reading and writing some 'dBase' files.
"Hit and Run" and "Shake and Bake" for Sampling Uniformly from Convex Shapes
The "Hit and Run" Markov Chain Monte Carlo method for sampling uniformly from convex shapes defined by linear constraints, and the "Shake and Bake" method for sampling from the boundary of such shapes. Includes specialized functions for sampling normalized weights with arbitrary linear constraints. Tervonen, T., van Valkenhoef, G., Basturk, N., and Postmus, D. (2012)