erblast
by erblast
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| Name | Latest Version | Summary | Updated | License |
|---|
| custom-r-bundle | 0.1.0 | — | Mar 25, 2025 | — |
| r-abind | 1.4_5 | Combine multidimensional arrays into a single array. This is a generalization of 'cbind' and 'rbind'. Works with vectors, matrices, and higher-dimensional arrays. Also provides functions 'adrop', 'asub', and 'afill' for manipulating, extracting and replacing data in arrays. | Mar 25, 2025 | LGPL (>= 2) |
| r-acepack | 1.4.1 | Two nonparametric methods for multiple regression transform selection are provided. The first, Alternative Conditional Expectations (ACE), is an algorithm to find the fixed point of maximal correlation, i.e. it finds a set of transformed response variables that maximizes R^2 using smoothing functions [see Breiman, L., and J.H. Friedman. 1985. "Estimating Optimal Transformations for Multiple Regression and Correlation". Journal of the American Statistical Association. 80:580-598. <doi:10.1080/01621459.1985.10478157>]. Also included is the Additivity Variance Stabilization (AVAS) method which works better than ACE when correlation is low [see Tibshirani, R.. 1986. "Estimating Transformations for Regression via Additivity and Variance Stabilization". Journal of the American Statistical Association. 83:394-405. <doi:10.1080/01621459.1988.10478610>]. A good introduction to these two methods is in chapter 16 of Frank Harrel's "Regression Modeling Strategies" in the Springer Series in Statistics. | Mar 25, 2025 | MIT + file LICENSE |
| r-adabag | 4.2 | It implements Freund and Schapire's Adaboost.M1 algorithm and Breiman's Bagging algorithm using classification trees as individual classifiers. Once these classifiers have been trained, they can be used to predict on new data. Also, cross validation estimation of the error can be done. Since version 2.0 the function margins() is available to calculate the margins for these classifiers. Also a higher flexibility is achieved giving access to the rpart.control() argument of 'rpart'. Four important new features were introduced on version 3.0, AdaBoost-SAMME (Zhu et al., 2009) is implemented and a new function errorevol() shows the error of the ensembles as a function of the number of iterations. In addition, the ensembles can be pruned using the option 'newmfinal' in the predict.bagging() and predict.boosting() functions and the posterior probability of each class for observations can be obtained. Version 3.1 modifies the relative importance measure to take into account the gain of the Gini index given by a variable in each tree and the weights of these trees. Version 4.0 includes the margin-based ordered aggregation for Bagging pruning (Guo and Boukir, 2013) and a function to auto prune the 'rpart' tree. Moreover, three new plots are also available importanceplot(), plot.errorevol() and plot.margins(). Version 4.1 allows to predict on unlabeled data. Version 4.2 includes the parallel computation option for some of the functions. | Mar 25, 2025 | GPL (>= 2) |
| r-assertthat | 0.2.1 | An extension to stopifnot() that makes it easy to declare the pre and post conditions that you code should satisfy, while also producing friendly error messages so that your users know what's gone wrong. | Mar 25, 2025 | GPL-3 |
| r-backports | 1.1.2 | Implementations of functions which have been introduced in R since version 3.0.0. The backports are conditionally exported which results in R resolving the function names to the version shipped with R (if available) and uses the implemented backports as fallback. This way package developers can make use of the new functions without worrying about the minimum required R version. | Mar 25, 2025 | GPL-2 |
| r-base | 3.5.1 | R is a free software environment for statistical computing and graphics. | Mar 25, 2025 | GPL-3.0 |
| r-base64enc | 0.1_3 | This package provides tools for handling base64 encoding. It is more flexible than the orphaned base64 package. | Mar 25, 2025 | GPL-2 | GPL-3 |
| r-bh | 1.69.0_1 | Boost provides free peer-reviewed portable C++ source libraries. A large part of Boost is provided as C++ template code which is resolved entirely at compile-time without linking. This package aims to provide the most useful subset of Boost libraries for template use among CRAN package. By placing these libraries in this package, we offer a more efficient distribution system for CRAN as replication of this code in the sources of other packages is avoided. As of release 1.69.0-1, the following Boost libraries are included: 'algorithm' 'align' 'any' 'atomic' 'bimap' 'bind' 'circular_buffer' 'compute' 'concept' 'config' 'container' 'date_time' 'detail' 'dynamic_bitset' 'exception' 'filesystem' 'flyweight' 'foreach' 'functional' 'fusion' 'geometry' 'graph' 'heap' 'icl' 'integer' 'interprocess' 'intrusive' 'io' 'iostreams' 'iterator' 'math' 'move' 'mpl' 'multiprcecision' 'numeric' 'pending' 'phoenix' 'preprocessor' 'propery_tree' 'random' 'range' 'scope_exit' 'smart_ptr' 'sort' 'spirit' 'tuple' 'type_traits' 'typeof' 'unordered' 'utility' 'uuid'. | Mar 25, 2025 | BSL-1.0 |
| r-bindr | 0.1.1 | Provides a simple interface for creating active bindings where the bound function accepts additional arguments. | Mar 25, 2025 | MIT + file LICENSE |
| r-bindrcpp | 0.2.2 | Provides an easy way to fill an environment with active bindings that call a C++ function. | Mar 25, 2025 | MIT + file LICENSE |
| r-bit | 1.1_14 | True boolean datatype (no NAs), coercion from and to logicals, integers and integer subscripts; fast boolean operators and fast summary statistics. With 'bit' vectors you can store true binary booleans {FALSE,TRUE} at the expense of 1 bit only, on a 32 bit architecture this means factor 32 less RAM and ~ factor 32 more speed on boolean operations. Due to overhead of R calls, actual speed gain depends on the size of the vector: expect gains for vectors of size > 10000 elements. Even for one-time boolean operations it can pay-off to convert to bit, the pay-off is obvious, when such components are used more than once. Reading from and writing to bit is approximately as fast as accessing standard logicals - mostly due to R's time for memory allocation. The package allows to work with pre-allocated memory for return values by calling .Call() directly: when evaluating the speed of C-access with pre-allocated vector memory, coping from bit to logical requires only 70% of the time for copying from logical to logical; and copying from logical to bit comes at a performance penalty of 150%. the package now contains further classes for representing logical selections: 'bitwhich' for very skewed selections and 'ri' for selecting ranges of values for chunked processing. All three index classes can be used for subsetting 'ff' objects (ff-2.1-0 and higher). | Mar 25, 2025 | GPL-2 |
| r-bit64 | 0.9_7 | Package 'bit64' provides serializable S3 atomic 64bit (signed) integers. These are useful for handling database keys and exact counting in +-2^63. WARNING: do not use them as replacement for 32bit integers, integer64 are not supported for subscripting by R-core and they have different semantics when combined with double, e.g. integer64 + double => integer64. Class integer64 can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, characters and factors as well as many elementwise and summary functions. Many fast algorithmic operations such as 'match' and 'order' support inter- active data exploration and manipulation and optionally leverage caching. | Mar 25, 2025 | GPL-2 |
| r-bitops | 1.0_6 | Functions for bitwise operations on integer vectors. | Mar 25, 2025 | GPL (>= 2) |
| r-blob | 1.1.0 | R's raw vector is useful for storing a single binary object. What if you want to put a vector of them in a data frame? The blob package provides the blob object, a list of raw vectors, suitable for use as a column in data frame. | Mar 25, 2025 | GPL-3 |
| r-boot | 1.3_20 | Functions and datasets for bootstrapping from the book "Bootstrap Methods and Their Application" by A. C. Davison and D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S. | Mar 25, 2025 | Unlimited |
| r-brew | 1.0_6 | brew implements a templating framework for mixing text and R code for report generation. brew template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module. | Mar 25, 2025 | GPL-2 |
| r-broom | 0.5.0 | Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures. | Mar 25, 2025 | MIT + file LICENSE |
| r-callr | 2.0.4 | It is sometimes useful to perform a computation in a separate R process, without affecting the current R process at all. This packages does exactly that. | Mar 25, 2025 | MIT + file LICENSE |
| r-caret | 6.0_80 | Misc functions for training and plotting classification and regression models. | Mar 25, 2025 | GPL (>= 2) |
| r-catools | 1.17.1.1 | Contains several basic utility functions including: moving (rolling, running) window statistic functions, read/write for GIF and ENVI binary files, fast calculation of AUC, LogitBoost classifier, base64 encoder/decoder, round-off-error-free sum and cumsum, etc. | Mar 25, 2025 | GPL-3 |
| r-cellranger | 1.1.0 | Helper functions to work with spreadsheets and the "A1:D10" style of cell range specification. | Mar 25, 2025 | MIT + file LICENSE |
| r-checkmate | 1.8.5 | Tests and assertions to perform frequent argument checks. A substantial part of the package was written in C to minimize any worries about execution time overhead. | Mar 25, 2025 | BSD_3_clause + file LICENSE |
| r-class | 7.3_14 | Various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps. | Mar 25, 2025 | GPL-2 | GPL-3 |
| r-classint | 0.1_24 | Selected commonly used methods for choosing univariate class intervals for mapping or other graphics purposes. | Mar 25, 2025 | GPL (>= 2) |