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r-pheval
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public |
Provides tools for the evaluation of the goodness of fit and the predictive capacity of the proportional hazards model.
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2023-06-16 |
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r-passport
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public |
Smooths the process of working with country names and codes via powerful parsing, standardization, and conversion utilities arranged in a simple, consistent API. Country name formats include multiple sources including the Unicode Common Locale Data Repository (CLDR, <http://cldr.unicode.org/>) common-sense standardized names in hundreds of languages.
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2023-06-16 |
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r-parallelmcmccombine
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Recent Bayesian Markov chain Monto Carlo (MCMC) methods have been developed for big data sets that are too large to be analyzed using traditional statistical methods. These methods partition the data into non-overlapping subsets, and perform parallel independent Bayesian MCMC analyses on the data subsets, creating independent subposterior samples for each data subset. These independent subposterior samples are combined through four functions in this package, including averaging across subset samples, weighted averaging across subsets samples, and kernel smoothing across subset samples. The four functions assume the user has previously run the Bayesian analysis and has produced the independent subposterior samples outside of the package; the functions use as input the array of subposterior samples. The methods have been demonstrated to be useful for Bayesian MCMC models including Bayesian logistic regression, Bayesian Gaussian mixture models and Bayesian hierarchical Poisson-Gamma models. The methods are appropriate for Bayesian hierarchical models with hyperparameters, as long as data values in a single level of the hierarchy are not split into subsets.
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2023-06-16 |
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r-pagenum
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public |
A simple way to add page numbers to base/ggplot/lattice graphics.
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2023-06-16 |
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r-outrankingtools
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public |
Functions to process ''outranking'' ELECTRE methods existing in the literature. See, e.g., <http://en.wikipedia.org/wiki/ELECTRE> about the outranking approach and the foundations of ELECTRE methods.
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2023-06-16 |
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r-orthogonalsplinebasis
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Represents the basis functions for B-splines in a simple matrix formulation that facilitates, taking integrals, derivatives, and making orthogonal the basis functions.
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2023-06-16 |
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r-ordinalnet
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public |
Fits ordinal regression models with elastic net penalty. Supported model families include cumulative probability, stopping ratio, continuation ratio, and adjacent category. These families are a subset of vector glm's which belong to a model class we call the elementwise link multinomial-ordinal (ELMO) class. Each family in this class links a vector of covariates to a vector of class probabilities. Each of these families has a parallel form, which is appropriate for ordinal response data, as well as a nonparallel form that is appropriate for an unordered categorical response, or as a more flexible model for ordinal data. The parallel model has a single set of coefficients, whereas the nonparallel model has a set of coefficients for each response category except the baseline category. It is also possible to fit a model with both parallel and nonparallel terms, which we call the semi-parallel model. The semi-parallel model has the flexibility of the nonparallel model, but the elastic net penalty shrinks it toward the parallel model. For details, refer to Wurm, Hanlon, and Rathouz (2017) <arXiv:1706.05003>.
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2023-06-16 |
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r-orcutt
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Solve first order autocorrelation problems using an iterative method. This procedure estimates both autocorrelation and beta coefficients recursively until we reach the convergence (8th decimal as default). The residuals are computed after estimating Beta using EGLS approach and Rho is estimated using the previous residuals.
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2023-06-16 |
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r-optifunset
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A single function 'options.ifunset(...)' is contained herewith, which allows the user to set a global option ONLY if it is not already set. By this token, for package maintainers this function can be used in preference to the standard 'options(...)' function, making provision for THEIR end user to place 'options(...)' directives within their '.Rprofile' file, which will not be overridden at the point when a package is loaded.
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2023-06-16 |
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r-oomisc
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public |
Includes miscellaneous functions.
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2023-06-16 |
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r-ohtadstats
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public |
Calculate's Tomoka Ohta's partitioning of linkage disequilibrium, deemed D-statistics, for pairs of loci. Beissinger et al. (2016) <doi:10.1038/hdy.2015.81>.
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2023-06-16 |
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r-odds.converter
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public |
Conversion between the most common odds types for sports betting. Hong Kong odds, US odds, Decimal odds, Indonesian odds, Malaysian odds, and raw Probability are covered in this package.
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2023-06-16 |
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r-nppbib
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public |
Implements a nonparametric statistical test for rank or score data from partially-balanced incomplete block-design experiments.
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2023-06-16 |
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r-npmvcp
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public |
Nonparametric Multivariate Change Point Model
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2023-06-16 |
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r-omd
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public |
This package including two useful function, which can be used for filter the molecular descriptors matrix for QSAR.
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2023-06-16 |
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r-oglmx
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Ordered models such as ordered probit and ordered logit presume that the error variance is constant across observations. In the case that this assumption does not hold estimates of marginal effects are typically biased (Weiss (1997)). This package allows for generalization of ordered probit and ordered logit models by allowing the user to specify a model for the variance. Furthermore, the package includes functions to calculate the marginal effects. Wrapper functions to estimate the standard limited dependent variable models are also included.
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2023-06-16 |
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r-numbers
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Provides number-theoretic functions for factorization, prime numbers, twin primes, primitive roots, modular logarithm and inverses, extended GCD, Farey series and continuous fractions. Includes Legendre and Jacobi symbols, some divisor functions, Euler's Phi function, etc.
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2023-06-16 |
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r-nsrr
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public |
Allows users to access data from the National Sleep Research Resource ('NSRR') <https://sleepdata.org/>.
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2023-06-16 |
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r-notemd
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public |
When building a 'shiny' app to generate reports (pdf or 'word'), we can insert a comment box in front-end side for user to write down them notes and use this package to document those notes in reports.
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-onnx
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R Interface to 'ONNX' - Open Neural Network Exchange <https://onnx.ai/>. 'ONNX' provides an open source format for machine learning models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
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2023-06-16 |
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r-onetwosamples
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In this package, we introduce an R function one_two_sample() which can deal with one and two (normal) samples. For one normal sample x, the function reports descriptive statistics, plot, interval estimation and test of hypothesis of x. For two normal samples x and y, the function reports descriptive statistics, plot, interval estimation and test of hypothesis of x and y, respectively. It also reports interval estimation and test of hypothesis of mu1-mu2 (the difference of the means of x and y) and sigma1^2 / sigma2^2 (the ratio of the variances of x and y), tests whether x and y are from the same population, finds the correlation coefficient of x and y if x and y have the same length.
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2023-06-16 |
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r-onage
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Implementation of a likelihood ratio test of differential onset of senescence between two groups. Given two groups with measures of age and of an individual trait likely to be subjected to senescence (e.g. body mass), 'OnAge' provides an asymptotic p-value for the null hypothesis that senescence starts at the same age in both groups. The package implements the procedure used in Douhard et al. (2017) <doi:10.1111/oik.04421>.
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2023-06-16 |
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r-ohit
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public |
Ing and Lai (2011) <doi:10.5705/ss.2010.081> proposed a high-dimensional model selection procedure that comprises three steps: orthogonal greedy algorithm (OGA), high-dimensional information criterion (HDIC), and Trim. The first two steps, OGA and HDIC, are used to sequentially select input variables and determine stopping rules, respectively. The third step, Trim, is used to delete irrelevant variables remaining in the second step. This package aims at fitting a high-dimensional linear regression model via OGA+HDIC+Trim.
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2023-06-16 |
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r-ogi
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Consider a data matrix of n individuals with p variates. The objective general index (OGI) is a general index that combines the p variates into a univariate index in order to rank the n individuals. The OGI is always positively correlated with each of the variates. More details can be found in Sei (2016) <doi:10.1016/j.jmva.2016.02.005>.
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2023-06-16 |
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r-odds.n.ends
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Computes odds ratios and 95% confidence intervals from a generalized linear model object. It also computes model significance with the chi-squared statistic and p-value and it computes model fit using a contingency table to determine the percent of observations for which the model correctly predicts the value of the outcome. Calculates model sensitivity and specificity.
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2023-06-16 |
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r-odata
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Helper methods for accessing data from web service based on OData Protocol. It provides several helper methods to access the service metadata, the data from datasets and to download some file resources (it only support CSV for now). For more information about OData go to <http://www.odata.org/documentation/>.
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2023-06-16 |
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r-nzelect
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Convenient access to New Zealand election results by voting place. Voting places have been matched to Regional Council, Territorial Authority, and Area Unit, to facilitate matching with additional data. Opinion polls since 2002 and some convenience analytical function are also supplied.
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2023-06-16 |
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r-npmlda
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Support the book: Wu CO and Tian X (2018). Nonparametric Models for Longitudinal Data. Chapman & Hall/CRC (to appear); and provide fit for using global and local smoothing methods for the conditional-mean and conditional-distribution based models with longitudinal Data.
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2023-06-16 |
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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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2023-06-16 |
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r-phtt
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The package provides estimation procedures for panel data with large dimensions n, T, and general forms of unobservable heterogeneous effects. Particularly, the estimation procedures are those of Bai (2009) and Kneip, Sickles, and Song (2012), which complement one another very well: both models assume the unobservable heterogeneous effects to have a factor structure. The method of Bai (2009) assumes that the factors are stationary, whereas the method of Kneip et al. (2012) allows the factors to be non-stationary. Additionally, the 'phtt' package provides a wide range of dimensionality criteria in order to estimate the number of the unobserved factors simultaneously with the remaining model parameters.
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2023-06-16 |
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r-ph2mult
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Provide multinomial design methods under intersection-union test (IUT) and union-intersection test (UIT) scheme for Phase II trial. The design types include : Minimax (minimize the maximum sample size), Optimal (minimize the expected sample size), Admissible (minimize the Bayesian risk) and Maxpower (maximize the exact power level).
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2023-06-16 |
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r-pgls
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Based on the Generalized Least Square model for comparative Phylogenetics (ref).
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2023-06-16 |
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r-pgee
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public |
Fits penalized generalized estimating equations to longitudinal data with high-dimensional covariates.
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2023-06-16 |
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r-pder
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public |
Data sets for the Panel Data Econometrics with R <doi:10.1002/9781119504641> book.
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2023-06-16 |
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r-pbimisc
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public |
A set of datasets and functions used in the book 'Modele liniowe i mieszane w R, wraz z przykladami w analizie danych'. Datasets either come from real studies or are created to be as similar as possible to real studies.
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2023-06-16 |
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r-parsetools
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Tools and utilities for dealing with parse data. Parse data represents the parse tree as data with location and type information. This package provides functions for navigating the parse tree as a data frame.
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2023-06-16 |
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r-parse
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public |
Model-based clustering and identifying informative features based on regularization methods. The package includes three regularization methods - PAirwise Reciprocal fuSE (PARSE) penalty proposed by Wang, Zhou and Hoeting (2016), the adaptive L1 penalty (APL1) and the adaptive pairwise fusion penalty (APFP). Heatmaps are included to shown the identification of informative features.
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2023-06-16 |
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r-panjen
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A central decision in a parametric regression is how to specify the relation between an dependent variable and each explanatory variable. This package provides a semi-parametric tool for comparing different transformations of an explanatory variables in a parametric regression. The functions is relevant in a situation, where you would use a box-cox or Box-Tidwell transformations. In contrast to the classic power-transformations, the methods in this package allows for theoretical driven user input and the possibility to compare with a non-parametric transformation.
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2023-06-16 |
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r-pakpmics2014ch
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Provides data set and functions for exploration of Multiple Indicator Cluster Survey (MICS) 2014 Child questionnaire data for Punjab, Pakistan (<http://www.mics.unicef.org/surveys>).
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2023-06-16 |
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r-pairwise
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Performs the explicit calculation -- not estimation! -- of the Rasch item parameters for dichotomous and polytomous item responses, using a pairwise comparison approach. Person parameters (WLE) are calculated according to Warm's weighted likelihood approach.
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2023-06-16 |
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r-pairheatmap
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A tool to compare two heatmaps and discover patterns within and across groups. In the context of biology, group can be defined based on gene ontology.
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2023-06-16 |
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r-pairedci
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The package contains two functions: paired.Loc and paired.Scale. A parametric and nonparametric confidence interval can be computed for the ratio of locations (paired.Loc) and the ratio of scales (paired.Scale). The samples must be paired and expected values must be positive.
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2023-06-16 |
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r-pabonlasso
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Pabon Lasso is a graphical method for monitoring the efficiency of different wards of a hospital or different hospitals.Pabon Lasso graph is divided into 4 parts which are created after drawing the average of BTR and BOR. The part in the left-down side is Zone I, left-up side is Zone II, Right-up side part is Zone III and the last part is Zone IV.
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2023-06-16 |
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r-outbreaks
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public |
Empirical or simulated disease outbreak data, provided either as RData or as text files.
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2023-06-16 |
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r-opi
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Implementation of the Open Perimetry Interface (OPI) for simulating and controlling visual field machines using R. The OPI is a standard for interfacing with visual field testing machines (perimeters). It specifies basic functions that allow many visual field tests to be constructed. As of October 2017 it is fully implemented on the Octopus 900 and partially on the Heidelberg Edge Perimeter, the Kowa AP 7000, the CrewT imo and the Centervue Compass. It also has a cousin: the R package 'visualFields', which has tools for analysing and manipulating visual field data.
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2023-06-16 |
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r-operators
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A set of binary operators for common tasks such as regex manipulation.
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2023-06-16 |
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r-odenetwork
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Simulates a network of ordinary differential equations of order two. The package provides an easy interface to construct networks. In addition you are able to define different external triggers to manipulate the trajectory. The method is described by Surmann, Ligges, and Weihs (2014) <doi:10.1109/ENERGYCON.2014.6850482>.
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2023-06-16 |
