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r-productplots
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Framework for visualising tables of counts, proportions and probabilities. The framework is called product plots, alluding to the computation of area as a product of height and width, and the statistical concept of generating a joint distribution from the product of conditional and marginal distributions. The framework, with extensions, is sufficient to encompass over 20 visualisations previously described in fields of statistical graphics and 'infovis', including bar charts, mosaic plots, 'treemaps', equal area plots and fluctuation diagrams.
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2025-04-22 |
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r-probably
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Models can be improved by post-processing class probabilities, by: recalibration, conversion to hard probabilities, assessment of equivocal zones, and other activities. 'probably' contains tools for conducting these operations as well as calibration tools and conformal inference techniques for regression models.
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2025-04-22 |
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r-pricer
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Functions to aid in micro and macro economic analysis and handling of price and currency data. Includes extraction of relevant inflation and exchange rate data from World Bank API, data cleaning/parsing, and standardisation. Inflation adjustment calculations as found in Principles of Macroeconomics by Gregory Mankiw et al (2014). Current and historical end of day exchange rates for 171 currencies from the European Central Bank Statistical Data Warehouse (2020) <https://sdw.ecb.europa.eu/curConverter.do>.
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2025-04-22 |
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r-preferably
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This is an accessible template for 'pkgdown'. It uses two bootstrap themes, Flatly and Darkly and utilizes the 'prefers-color-scheme' CSS variable to automatically serve either of the two based on user’s operating system setting, or allowing them to manually toggle between them.
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2025-04-22 |
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r-predicts
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Methods for spatial predictive modeling, especially for spatial distribution models. This includes algorithms for model fitting and prediction, as well as methods for model evaluation.
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2025-04-22 |
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r-pre
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Derives prediction rule ensembles (PREs). Largely follows the procedure for deriving PREs as described in Friedman & Popescu (2008; <DOI:10.1214/07-AOAS148>), with adjustments and improvements. The main function pre() derives prediction rule ensembles consisting of rules and/or linear terms for continuous, binary, count, multinomial, and multivariate continuous responses. Function gpe() derives generalized prediction ensembles, consisting of rules, hinge and linear functions of the predictor variables.
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2025-04-22 |
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r-predictabel
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We included functions to assess the performance of risk models. The package contains functions for the various measures that are used in empirical studies, including univariate and multivariate odds ratios (OR) of the predictors, the c-statistic (or area under the receiver operating characteristic (ROC) curve (AUC)), Hosmer-Lemeshow goodness of fit test, reclassification table, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Also included are functions to create plots, such as risk distributions, ROC curves, calibration plot, discrimination box plot and predictiveness curves. In addition to functions to assess the performance of risk models, the package includes functions to obtain weighted and unweighted risk scores as well as predicted risks using logistic regression analysis. These logistic regression functions are specifically written for models that include genetic variables, but they can also be applied to models that are based on non-genetic risk factors only. Finally, the package includes function to construct a simulated dataset with genotypes, genetic risks, and disease status for a hypothetical population, which is used for the evaluation of genetic risk models.
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2025-04-22 |
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r-powertost
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Contains functions to calculate power and sample size for various study designs used in bioequivalence studies. Use known.designs() to see the designs supported. Power and sample size can be obtained based on different methods, amongst them prominently the TOST procedure (two one-sided t-tests). See README and NEWS for further information.
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2025-04-22 |
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r-potools
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Translating messages in R packages is managed using the po top-level directory and the 'gettext' program. This package provides some helper functions for building this support in R packages, e.g. common validation & I/O tasks.
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2025-04-22 |
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r-portes
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Contains common univariate and multivariate portmanteau test statistics for time series models. These tests are based on using asymptotic distributions such as chi-square distribution and based on using the Monte Carlo significance tests. Also, it can be used to simulate from univariate and multivariate seasonal time series models.
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2025-04-22 |
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r-portfoliobacktest
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Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots.
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2025-04-22 |
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r-popgenreport
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Provides beginner friendly framework to analyse population genetic data. Based on 'adegenet' objects it uses 'knitr' to create comprehensive reports on spatial genetic data. For detailed information how to use the package refer to the comprehensive tutorials or visit <http://www.popgenreport.org/>.
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2025-04-22 |
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r-poorman
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A replication of key functionality from 'dplyr' and the wider 'tidyverse' using only 'base'.
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2025-04-22 |
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r-popepi
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Enables computation of epidemiological statistics, including those where counts or mortality rates of the reference population are used. Currently supported: excess hazard models (Dickman, Sloggett, Hills, and Hakulinen (2012) <doi:10.1002/sim.1597>), rates, mean survival times, relative/net survival (in particular the Ederer II (Ederer and Heise (1959)) and Pohar Perme (Pohar Perme, Stare, and Esteve (2012) <doi:10.1111/j.1541-0420.2011.01640.x>) estimators), and standardized incidence and mortality ratios, all of which can be easily adjusted for by covariates such as age. Fast splitting and aggregation of 'Lexis' objects (from package 'Epi') and other computations achieved using 'data.table'.
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2025-04-22 |
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r-popdemo
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Tools for modelling populations and demography using matrix projection models, with deterministic and stochastic model implementations. Includes population projection, indices of short- and long-term population size and growth, perturbation analysis, convergence to stability or stationarity, and diagnostic and manipulation tools.
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2025-04-22 |
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r-polychrome
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Tools for creating, viewing, and assessing qualitative palettes with many (20-30 or more) colors. See Coombes and colleagues (2019) <doi:10.18637/jss.v090.c01>.
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2025-04-22 |
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r-pollster
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Calculate common types of tables for weighted survey data. Options include topline and (2-way and 3-way) crosstab tables of categorical or ordinal data as well as summary tables of weighted numeric variables. Optionally, include the margin of error at selected confidence intervals including the design effect. The design effect is calculated as described by Kish (1965) <doi:10.1002/bimj.19680100122> beginning on page 257. Output takes the form of tibbles (simple data frames). This package conveniently handles labelled data, such as that commonly used by 'Stata' and 'SPSS.' Complex survey design is not supported at this time.
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2025-04-22 |
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r-polite
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Be responsible when scraping data from websites by following polite principles: introduce yourself, ask for permission, take slowly and never ask twice.
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2025-04-22 |
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r-poliscidata
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Bundles the datasets and functions used in the textbook by Philip Pollock and Barry Edwards, an R Companion to Essentials of Political Analysis, Second Edition.
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2025-04-22 |
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r-pointblank
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Validate data in data frames, 'tibble' objects, 'Spark' 'DataFrames', and database tables. Validation pipelines can be made using easily-readable, consecutive validation steps. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions. Many other workflows are available including an information management workflow, where the aim is to record, collect, and generate useful information on data tables.
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2025-04-22 |
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r-pnadcibge
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Provides tools for downloading, reading and analyzing the PNADC, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
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2025-04-22 |
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r-plsrglm
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Provides (weighted) Partial least squares Regression for generalized linear models and repeated k-fold cross-validation of such models using various criteria <arXiv:1810.01005>. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.
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2025-04-22 |
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r-plspm
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Partial Least Squares Path Modeling (PLS-PM), Tenenhaus, Esposito Vinzi, Chatelin, Lauro (2005) <doi:10.1016/j.csda.2004.03.005>, analysis for both metric and non-metric data, as well as REBUS analysis, Esposito Vinzi, Trinchera, Squillacciotti, and Tenenhaus (2008) <doi:10.1002/asmb.728>.
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2025-04-22 |
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r-plottools
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Annotate plots with legends for continuous variables and colour spectra using the base graphics plotting tools; and manipulate irregular polygons.
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2025-04-22 |
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r-plotrcs
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Simple drawing of restricted cubic spline (RCS) curves through 'ggplot2' package from a linear regression model, a logistic regression model or a Cox proportional hazards regression model. This method was described by Harrell FE (2015) <doi:10.1007/978-3-319-19425-7>.
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2025-04-22 |
