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r-vigor
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Conducts linear regression using variational Bayesian inference, particularly optimized for genome-wide association mapping and whole-genome prediction which use a number of DNA markers as the explanatory variables. Provides seven regression models which select the important variables (i.e., the variables related to response variables) among the given explanatory variables in different ways (i.e., model structures).
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2025-04-22 |
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r-vifcp
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Contains a function to support the following paper: Xiaoping Shi, Xiang-Sheng Wang, Dongwei Wei, Yuehua Wu (2016), <DOI:10.1007/s00180-015-0587-5>, A sequential multiple change-point detection procedure via VIF regression, Computational Statistics, 31(2): 671-691.
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2025-04-22 |
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r-vicmodel
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The Variable Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW). The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>, see Hamman et al. (2018). Development and maintenance of the current official version of the VIC model at present is led by the UW Hydro (Computational Hydrology group) in the Department of Civil and Environmental Engineering at UW. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as globally. If you make use of this model, please acknowledge the appropriate references listed in the help page of this package or on the references page <http://vic.readthedocs.io/en/master/Documentation/References/> of the VIC official documentation website. These should include Liang et al. (1994) plus any references relevant to the features you are using Reference: Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, <doi:10.1029/94JD00483>. Hamman et al. (2018) about VIC 5.0.1 also can be considered: Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, <doi:10.5194/gmd-11-3481-2018>.
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2025-04-22 |
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r-vgamextra
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Extending the functionalities of the 'VGAM' package with additional functions and datasets. At present, 'VGAMextra' comprises new family functions (ffs) to estimate several time series models by maximum likelihood using Fisher scoring, unlike popular packages in CRAN relying on optim(), including ARMA-GARCH-like models, the Order-(p, d, q) ARIMAX model (non- seasonal), the Order-(p) VAR model, error correction models for cointegrated time series, and ARMA-structures with Student-t errors. For independent data, new ffs to estimate the inverse- Weibull, the inverse-gamma, the generalized beta of the second kind and the general multivariate normal distributions are available. In addition, 'VGAMextra' incorporates new VGLM-links for the mean-function, and the quantile-function (as an alternative to ordinary quantile modelling) of several 1-parameter distributions, that are compatible with the class of VGLM/VGAM family functions. Currently, only fixed-effects models are implemented. All functions are subject to change; see the NEWS for further details on the latest changes.
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2025-04-22 |
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r-vetr
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Declarative template-based framework for verifying that objects meet structural requirements, and auto-composing error messages when they do not.
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2025-04-22 |
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r-verylargeintegers
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Multi-precision library that allows to store and operate with arbitrarily big integers without loss of precision. It includes a large list of tools to work with them, like: - Arithmetic and logic operators - Modular-arithmetic operators - Computer Number Theory utilities - Probabilistic primality tests - Factorization algorithms - Random generators of diferent types of integers.
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2025-04-22 |
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r-vdgraph
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Uses a modification of the published FORTRAN code in "A Computer Program for Generating Variance Dispersion Graphs" by G. Vining, Journal of Quality Technology, Vol. 25 No. 1 January 1993, to produce variance dispersion graphs. Also produces fraction of design space plots, and contains data frames for several minimal run response surface designs.
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2025-04-22 |
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r-vca
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ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.
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2025-04-22 |
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r-vbsr
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Efficient algorithm for solving ultra-sparse regularized regression models using a variational Bayes algorithm with a spike (l0) prior. Algorithm is solved on a path, with coordinate updates, and is capable of generating very sparse models. There are very general model diagnostics for controling type-1 error included in this package.
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2025-04-22 |
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r-vbdm
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Efficient algorithm for solving discrete mixture regression model for rare variant association analysis. Uses variational Bayes algorithm to efficiently search over model space. Outputs an approximate likelihood ratio test as well as variant level posterior probabilities of association.
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2025-04-22 |
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r-varband
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Implementation of the variable banding procedure for modeling local dependence and estimating precision matrices that is introduced in Yu & Bien (2016) and is available at <https://arxiv.org/abs/1604.07451>.
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2025-04-22 |
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r-valorate
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The algorithm implemented in this package was designed to quickly estimates the distribution of the log-rank especially for heavy unbalanced groups. VALORATE estimates the null distribution and the p-value of the log-rank test based on a recent formulation. For a given number of alterations that define the size of survival groups, the estimation involves a weighted sum of distributions that are conditional on a co-occurrence term where mutations and events are both present. The estimation of conditional distributions is quite fast allowing the analysis of large datasets in few minutes <http://bioinformatica.mty.itesm.mx/valorate>.
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2025-04-22 |
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r-validatejsonr
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The current implementation uses the C++ library 'RapidJSON' to supply the schema functionality, it supports JSON Schema Draft v4. As of 2016-09-09, 'RapidJSON' passed 262 out of 263 tests in JSON Schema Test Suite (JSON Schema draft 4).
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2025-04-22 |
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r-unsystation
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Performs a test for second-order stationarity of time series based on unsystematic sub-samples.
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2025-04-22 |
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r-unmarked
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Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) <doi:10.1111/2041-210X.14123>, Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.
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2025-04-22 |
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r-unix
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Bindings to system utilities found in most Unix systems such as POSIX functions which are not part of the Standard C Library.
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2025-04-22 |
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r-unine
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Implementation of "light" stemmers for French, German, Italian, Spanish, Portuguese, Finnish, Swedish. They are based on the same work as the "light" stemmers found in 'SolR' <https://lucene.apache.org/solr/> or 'ElasticSearch' <https://www.elastic.co/fr/products/elasticsearch>. A "light" stemmer consists in removing inflections only for noun and adjectives. Indexing verbs for these languages is not of primary importance compared to nouns and adjectives. The stemming procedure for French is described in (Savoy, 1999) <doi:10.1002/(SICI)1097-4571(1999)50:10%3C944::AID-ASI9%3E3.3.CO;2-H>.
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2025-04-22 |
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r-uniisoregression
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Perform L1 or L2 isotonic and unimodal regression on 1D weighted or unweighted input vector and isotonic regression on 2D weighted or unweighted input vector. It also performs L infinity isotonic and unimodal regression on 1D unweighted input vector. Reference: Quentin F. Stout (2008) <doi:10.1016/j.csda.2008.08.005>. Spouge, J., Wan, H. & Wilbur, W.(2003) <doi:10.1023/A:1023901806339>. Q.F. Stout (2013) <doi:10.1007/s00453-012-9628-4>.
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2025-04-22 |
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r-unifed
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Probability functions, family for glm() and Stan code for working with the unifed distribution (Quijano Xacur, 2019; <doi:10.1186/s40488-019-0102-6>).
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2025-04-22 |
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r-unidoe
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Efficient procedures for constructing uniform design of experiments under various space-filling criteria. It is based on a stochastic and adaptive threshold accepting algorithm with flexible initialization, adaptive threshold, and stochastic evolution. The package may also construct the augmented uniform designs in a sequential manner.
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2025-04-22 |
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r-unfoldr
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Stereological unfolding of the joint size-shape-orientation distribution of spheroidal shaped particles.
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2025-04-22 |
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r-ump
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Does uniformly most powerful (UMP) and uniformly most powerful unbiased (UMPU) tests. At present only distribution implemented is binomial distribution. Also does fuzzy tests and confidence intervals (following Geyer and Meeden, 2005, <doi:10.1214/088342305000000340>) for the binomial distribution (one-tailed procedures based on UMP test and two-tailed procedures based on UMPU test).
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2025-04-22 |
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r-ulid
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Universally unique identifiers ('UUIDs') can be suboptimal for many uses-cases because they aren't the most character efficient way of encoding 128 bits of randomness; v1/v2 versions are impractical in many environments, as they require access to a unique, stable MAC address; v3/v5 versions require a unique seed and produce randomly distributed IDs, which can cause fragmentation in many data structures; v4 provides no other information than randomness which can cause fragmentation in many data structures. 'ULIDs' (<https://github.com/ulid/spec>) have 128-bit compatibility with 'UUID', 1.21e+24 unique 'ULIDs' per millisecond, are lexicographically sortable, canonically encoded as a 26 character string, as opposed to the 36 character 'UUID', use Crockford's 'base32' for better efficiency and readability (5 bits per character), are case insensitive, have no special characters (i.e. are 'URL' safe) and have a onotonic sort order (correctly detects and handles the same millisecond).
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2025-04-22 |
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r-udpipe
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This natural language processing toolkit provides language-agnostic 'tokenization', 'parts of speech tagging', 'lemmatization' and 'dependency parsing' of raw text. Next to text parsing, the package also allows you to train annotation models based on data of 'treebanks' in 'CoNLL-U' format as provided at <https://universaldependencies.org/format.html>. The techniques are explained in detail in the paper: 'Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe', available at <doi:10.18653/v1/K17-3009>. The toolkit also contains functionalities for commonly used data manipulations on texts which are enriched with the output of the parser. Namely functionalities and algorithms for collocations, token co-occurrence, document term matrix handling, term frequency inverse document frequency calculations, information retrieval metrics (Okapi BM25), handling of multi-word expressions, keyword detection (Rapid Automatic Keyword Extraction, noun phrase extraction, syntactical patterns) sentiment scoring and semantic similarity analysis.
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2025-04-22 |
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r-ucminf
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An algorithm for general-purpose unconstrained non-linear optimization. The algorithm is of quasi-Newton type with BFGS updating of the inverse Hessian and soft line search with a trust region type monitoring of the input to the line search algorithm. The interface of 'ucminf' is designed for easy interchange with 'optim'.
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2025-04-22 |
