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r-nose
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The nose package consists of a collection of three functions for classifying sparseness in typical 2 x 2 data sets with at least one cell should have zero count. These functions are based on the three widely applied summary measures for 2 x 2 categorical data viz, Risk Difference (RD), Relative Risk (RR), Odds Ratio (OR). This package helps to identify suitable continuity correction for zero cells when a multi centre analysis or a meta analysis is carried out. Further, it can be considered as a tool for sensitivity analysis for adding a continuity correction and to identify the presence of Simpson's paradox.
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2025-04-22 |
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r-nortest
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Five omnibus tests for testing the composite hypothesis of normality.
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2025-04-22 |
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r-nortara
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An implementation of a specific method for generating n-dimensional random vectors with given marginal distributions and correlation matrix. The method uses the NORTA (NORmal To Anything) approach which generates a standard normal random vector and then transforms it into a random vector with specified marginal distributions and the RA (Retrospective Approximation) algorithm which is a generic stochastic root-finding algorithm. The marginals can be continuous or discrete. See the vignette of package for more details.
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2025-04-22 |
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r-normwhn.test
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Includes Omnibus Univariate and Multivariate Normality Tests (See Doornik and Hansen (1994)). One variation allows for the possibility of weak dependence rather than independence in the variable(s). Also included is an univariate white noise test where the null hypothesis is "white noise" rather than strict "white noise".
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2025-04-22 |
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r-normtest
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Tests for the composite hypothesis of normality
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2025-04-22 |
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r-normexpression
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It provides a framework and a fast and simple way for researchers to evaluate methods (particularly some data-driven methods or their own methods) and then select a best one for data normalization in the gene expression analysis, based on the consistency of metrics and the consistency of datasets. Zhenfeng Wu, Weixiang Liu, Xiufeng Jin, Deshui Yu, Hua Wang, Gustavo Glusman, Max Robinson, Lin Liu, Jishou Ruan and Shan Gao (2018) <doi:10.1101/251140>.
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2025-04-22 |
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r-normalr
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The robustness of many of the statistical techniques, such as factor analysis, applied in the social sciences rests upon the assumption of item-level normality. However, when dealing with real data, these assumptions are often not met. The Box-Cox transformation (Box & Cox, 1964) <http://www.jstor.org/stable/2984418> provides an optimal transformation for non-normal variables. Yet, for large datasets of continuous variables, its application in current software programs is cumbersome with analysts having to take several steps to normalise each variable. We present an R package 'normalr' that enables researchers to make convenient optimal transformations of multiple variables in datasets. This R package enables users to quickly and accurately: (1) anchor all of their variables at 1.00, (2) select the desired precision with which the optimal lambda is estimated, (3) apply each unique exponent to its variable, (4) rescale resultant values to within their original X1 and X(n) ranges, and (5) provide original and transformed estimates of skewness, kurtosis, and other inferential assessments of normality.
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2025-04-22 |
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r-normalp
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Collection of utilities referred to Exponential Power distribution, also known as General Error Distribution (see Mineo, A.M. and Ruggieri, M. (2005), A software Tool for the Exponential Power Distribution: The normalp package. In Journal of Statistical Software, Vol. 12, Issue 4).
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2025-04-22 |
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r-nordklimdata1
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The Nordklim dataset 1.0 is a unique and useful achievement for climate analysis. It includes observations of twelve different climate elements from more than 100 stations in the Nordic region, in time span over 100 years. The project contractors were NORDKLIM/NORDMET on behalf of the National meteorological services in Denmark (DMI), Finland (FMI), Iceland (VI), Norway (DNMI) and Sweden (SMHI).
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2025-04-22 |
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r-nor1mix
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Onedimensional Normal (i.e. Gaussian) Mixture Models Classes, for, e.g., density estimation or clustering algorithms research and teaching; providing the widely used Marron-Wand densities. Efficient random number generation and graphics. Fitting to data by efficient ML (Maximum Likelihood) or traditional EM estimation.
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2025-04-22 |
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r-nontargetdata
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Data sets for isotope pattern grouping of LC-HRMS peaks with package nontarget. Based on a vast set of unique PubChem molecular formulas, quantized (a) m/z, (b) m/z differences, (c) intensity ratios and (d) marker centroids of simulated centroid pairs are listed for different instrument resolutions.
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2025-04-22 |
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r-nonpareil
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Plot, process, and analyze NPO files produced by 'Nonpareil' <http://enve-omics.ce.gatech.edu/nonpareil>.
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2025-04-22 |
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r-nonpar
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Contains the following 5 nonparametric hypothesis tests: The Sign Test, The 2 Sample Median Test, Miller's Jackknife Procedure, Cochran's Q Test, & The Stuart-Maxwell Test.
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2025-04-22 |
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r-nonnormvtdist
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Implements calculation of probability density function, cumulative distribution function, equicoordinate quantile function and survival function, and random numbers generation for the following multivariate distributions: Lomax (Pareto Type II), generalized Lomax, Mardia’s Pareto of Type I, Logistic, Burr, Cook-Johnson’s uniform, F and Inverted Beta. See Tapan Nayak (1987) <doi:10.2307/3214068>.
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2025-04-22 |
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r-nonnest2
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Testing non-nested models via theory supplied by Vuong (1989) <DOI:10.2307/1912557>. Includes tests of model distinguishability and of model fit that can be applied to both nested and non-nested models. Also includes functionality to obtain confidence intervals associated with AIC and BIC. This material is partially based on work supported by the National Science Foundation under Grant Number SES-1061334.
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2025-04-22 |
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r-noncompart
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Conduct a noncompartmental analysis as closely as possible to the most widely used commercial software for pharmacokinetic analysis, i.e. 'Phoenix(R) WinNonlin(R)' <https://www.certara.com/software/pkpd-modeling-and-simulation/phoenix-winnonlin/>. Some features are 1) Use of CDISC SDTM terms 2) Automatic slope selection with the same criterion of WinNonlin(R) 3) Supporting both 'linear-up linear-down' and 'linear-up log-down' method 4) Interval(partial) AUCs with 'linear' or 'log' interpolation method * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107).
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2025-04-22 |
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r-noncensus
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A collection of various regional information determined by the U.S. Census Bureau along with demographic data.
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2025-04-22 |
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r-nomnoml
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A tool for drawing sassy 'UML' diagrams based on a simple syntax, see <http://www.nomnoml.com>. Supports styling, R Markdown and exporting diagrams in the PNG format.
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2025-04-22 |
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r-nomclust
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Package for hierarchical clustering of objects characterized by nominal variables.
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2025-04-22 |
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r-noisyce2
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Cross-Entropy optimisation of unconstrained deterministic and noisy functions illustrated in Rubinstein and Kroese (2004, ISBN: 978-1-4419-1940-3) through a highly flexible and customisable function which allows user to define custom variable domains, sampling distributions, updating and smoothing rules, and stopping criteria. Several built-in methods and settings make the package very easy-to-use under standard optimisation problems.
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2025-04-22 |
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r-noia
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The NOIA model, as described extensively in Alvarez-Castro & Carlborg (2007), is a framework facilitating the estimation of genetic effects and genotype-to-phenotype maps. This package provides the basic tools to perform linear and multilinear regressions from real populations (provided the phenotype and the genotype of every individuals), estimating the genetic effects from different reference points, the genotypic values, and the decomposition of genetic variances in a multi-locus, 2 alleles system. This package is presented in Le Rouzic & Alvarez-Castro (2008).
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2025-04-22 |
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r-pbdprof
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MPI profiling tools.
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2025-04-22 |
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r-pdfestimator
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Farmer, J., D. Jacobs (2108) <DOI:10.1371/journal.pone.0196937>. A nonparametric density estimator based on the maximum-entropy method. Accurately predicts a probability density function (PDF) for random data using a novel iterative scoring function to determine the best fit without overfitting to the sample.
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2025-04-22 |
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r-pdc
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Permutation Distribution Clustering is a clustering method for time series. Dissimilarity of time series is formalized as the divergence between their permutation distributions. The permutation distribution was proposed as measure of the complexity of a time series.
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2025-04-22 |
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r-pcit
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Apply Partial Correlation coefficient with Information Theory (PCIT) to a correlation matrix. The PCIT algorithm identifies meaningful correlations to define edges in a weighted network. The algorithm can be applied to any correlation-based network including but not limited to gene co-expression networks. To reduce compute time by making use of multiple compute cores, simply run PCIT on a computer with has multiple cores and also has the Rmpi package installed. PCIT will then auto-detect the multicore environment and run in parallel mode without the need to rewrite your scripts. This makes scripts, using PCIT, portable across single core (or no Rmpi package installed) computers which will run in serial mode and multicore (with Rmpi package installed) computers which will run in parallel mode.
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2025-04-22 |
