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r-pop
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public |
Population dynamic models underpin a range of analyses and applications in ecology and epidemiology. The various approaches for analysing population dynamics models (MPMs, IPMs, ODEs, POMPs, PVA) each require the model to be defined in a different way. This makes it difficult to combine different modelling approaches and data types to solve a given problem. 'pop' aims to provide a flexible and easy to use common interface for constructing population dynamic models and enabling to them to be fitted and analysed in lots of different ways.
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2025-04-22 |
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r-poolfstat
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public |
Functions for the computation of F-statistics from Pool-Seq data in population genomics studies. The package also includes several utilities to manipulate Pool-Seq data stored in standard format ('vcf' or 'rsync' files generated by the the 'PoPoolation' software) and perform conversion to alternative format (as used in the 'BayPass' and 'SelEstim' software).
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2025-04-22 |
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r-pooledmeangroup
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Calculates the pooled mean group (PMG) estimator for dynamic panel data models, as described by Pesaran, Shin and Smith (1999) <doi:10.1080/01621459.1999.10474156>.
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2025-04-22 |
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r-pomic
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Calculations of an information criterion are proposed to check the quality of simulations results of Agent-based models (ABM/IBM) or other non-linear rule-based models. The POMDEV measure (Pattern Oriented Modelling DEViance) is based on the Kullback-Leibler divergence and likelihood theory. It basically indicates the deviance of simulation results from field observations. Once POMDEV scores and metropolis-hasting sampling on different model versions are effectuated, POMIC scores (Pattern Oriented Modelling Information Criterion) can be calculated. This method could be further developed to incorporate multiple patterns assessment. Piou C, U Berger and V Grimm (2009) <doi:10.1016/j.ecolmodel.2009.05.003>.
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2025-04-22 |
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r-polytrend
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This algorithm classifies the trends into linear, quadratic, cubic, concealed and no-trend types. The "concealed trends" are those trends that possess quadratic or cubic forms, but the net change from the start of the time period to the end of the time period hasn't been significant. The "no-trend" category includes simple linear trends with statistically in-significant slope coefficient.
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2025-04-22 |
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r-polysegratio
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Perform classic chi-squared tests and Ripol et al(1999) binomial confidence interval approach for autopolyploid dominant markers. Also, dominant markers may be generated for families of offspring where either one or both of the parents possess the marker. Missing values and misclassified markers may be generated at random.
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2025-04-22 |
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r-polypatex
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Functions to perform paternity exclusion via allele matching, in autopolyploid species having ploidy 4, 6, or 8. The marker data used can be genotype data (copy numbers known) or 'allelic phenotype data' (copy numbers not known).
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2025-04-22 |
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r-polynom
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A collection of functions to implement a class for univariate polynomial manipulations.
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2025-04-22 |
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r-polycor
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Computes polychoric and polyserial correlations by quick "two-step" methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases.
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2025-04-22 |
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r-polyaaeppli
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public |
Functions for evaluating the mass density, cumulative distribution function, quantile function and random variate generation for the Polya-Aeppli distribution, also known as the geometric compound Poisson distribution.
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2025-04-22 |
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r-pollstr
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Client for the HuffPost Pollster API, which provides access to U.S. polls on elections and political opinion.
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2025-04-22 |
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r-politicaldata
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public |
Provides useful functions for obtaining commonly-used data in political analysis and political science, including from sources such as the Comparative Agendas Project <https://www.comparativeagendas.net>, which provides data on politics and policy from 20+ countries, the MIT Election and Data Science Lab <https://www.electionlab.mit.edu>, and FiveThirtyEight <https://www.FiveThirtyEight.com>.
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2025-04-22 |
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r-polidata
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This package provides easy access to various political data APIs directly from R. For example, you can access Google Civic Information API <https://developers.google.com/civic-information/> or Sunlight Congress API <https://sunlightlabs.github.io/congress/> for US Congress data, and POPONG API <http://data.popong.com/> for South Korea National Assembly data.
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2025-04-22 |
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r-poker
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Type testRoundOfPoker() to demonstrate the game of Texas Hold ‘Em poker. Rotate the dealer button, deal cards, rank each hand, compare ranks, break ties (if necessary), determine the winner, output a textual summary, and output a graphical user interface.
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2025-04-22 |
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r-poistweedie
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Simulation of models Poisson-Tweedie.
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2025-04-22 |
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r-poissonseq
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public |
This package implements a method for normalization, testing, and false discovery rate estimation for RNA-sequencing data. The description of the method is in Li J, Witten DM, Johnstone I, Tibshirani R (2012). Normalization, testing, and false discovery rate estimation for RNA-sequencing data. Biostatistics 13(3): 523-38. We estimate the sequencing depths of experiments using a new method based on Poisson goodness-of-fit statistic, calculate a score statistic on the basis of a Poisson log-linear model, and then estimate the false discovery rate using a modified version of permutation plug-in method. A more detailed instruction as well as sample data is available at http://www.stanford.edu/~junli07/research.html. In this version, we changed the way of calculating log foldchange for two-class data. The FDR estimation part remains unchanged.
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2025-04-22 |
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r-poisson.glm.mix
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High dimensional mixtures of Poisson Generalized Linear models with three different parameterizations of Poisson means are considered. Moreover, partitioning the response variables into a set of blocks is possible. The package estimates parameters via EM algorithm. For an efficient initialization, a random splitting small-EM is introduced.
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2025-04-22 |
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r-poisson
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Contains functions and classes for simulating, plotting and analysing homogenous and non-homogenous Poisson processes.
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2025-04-22 |
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r-poisnor
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Generates multivariate data with count and continuous variables with a pre-specified correlation matrix. The count and continuous variables are assumed to have Poisson and normal marginals, respectively. The data generation mechanism is a combination of the normal to anything principle and a connection between Poisson and normal correlations in the mixture.
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2025-04-22 |
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r-poisnonnor
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Generation of count (assuming Poisson distribution) and continuous data (using Fleishman polynomials) simultaneously.
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2025-04-22 |
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r-poisbinnonnor
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Generation of multiple count, binary and continuous variables simultaneously given the marginal characteristics and association structure. Throughout the package, the word 'Poisson' is used to imply count data under the assumption of Poisson distribution.
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2025-04-22 |
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r-pointdensityp
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The function pointdensity returns a density count and the temporal average for every point in the original list. The dataframe returned includes four columns: lat, lon, count, and date_avg. The "lat" column is the original latitude data; the "lon" column is the original longitude data; the "count" is the density count of the number of points within a radius of radius*grid_size (the neighborhood); and the date_avg column includes the average date of each point in the neighborhood.
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2025-04-22 |
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r-poiclaclu
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Implements the methods described in the paper, Witten (2011) Classification and Clustering of Sequencing Data using a Poisson Model, Annals of Applied Statistics 5(4) 2493-2518.
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2025-04-22 |
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r-poet
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Estimate large covariance matrices in approximate factor models by thresholding principal orthogonal complements.
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2025-04-22 |
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r-pod
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This tool computes the probability of detection (POD) curve and the limit of detection (LOD), i.e. the number of copies of the target DNA sequence required to ensure a 95 % probability of detection (LOD95). Other quantiles of the LOD can be specified. This is a reimplementation of the mathematical-statistical modelling of the validation of qualitative polymerase chain reaction (PCR) methods within a single laboratory as provided by the commercial tool 'PROLab' <http://quodata.de/>. The modelling itself has been described by Uhlig et al. (2015) <doi:10.1007/s00769-015-1112-9>.
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2025-04-22 |
