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r-ecovirtual
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public |
Computer simulations of classical ecological models as a learning resource.
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2024-01-16 |
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r-ed50
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public |
Functions of five estimation method for ED50 (50 percent effective dose) are provided, and they are respectively Dixon-Mood method (1948) <doi:10.2307/2280071>, Choi's original turning point method (1990) <doi:10.2307/2531453> and it's modified version given by us, as well as logistic regression and isotonic regression. Besides, the package also supports comparison between two estimation results.
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2024-01-16 |
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r-ecotoxicology
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public |
Implementation of the EPA's Ecological Exposure Research Division (EERD) tools (discontinued in 1999) for Probit and Trimmed Spearman-Karber Analysis. Probit and Spearman-Karber methods from Finney's book "Probit analysis a statistical treatment of the sigmoid response curve" with options for most accurate results or identical results to the book. Probit and all the tables from Finney's book (code-generated, not copied) with the generating functions included. Control correction: Abbott, Schneider-Orelli, Henderson-Tilton, Sun-Shepard. Toxicity scales: Horsfall-Barratt, Archer, Gauhl-Stover, Fullerton-Olsen, etc.
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2024-01-16 |
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r-ecotroph
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public |
An approach and software for modelling marine and freshwater ecosystems. It is articulated entirely around trophic levels. EcoTroph's key displays are bivariate plots, with trophic levels as the abscissa, and biomass flows or related quantities as ordinates. Thus, trophic ecosystem functioning can be modelled as a continuous flow of biomass surging up the food web, from lower to higher trophic levels, due to predation and ontogenic processes. Such an approach, wherein species as such disappear, may be viewed as the ultimate stage in the use of the trophic level metric for ecosystem modelling, providing a simplified but potentially useful caricature of ecosystem functioning and impacts of fishing. This version contains catch trophic spectrum analysis (CTSA) function and corrected versions of the mf.diagnosis and create.ETmain functions.
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2024-01-16 |
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r-ecm
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public |
Functions for easy building of error correction models (ECM) for time series regression.
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2024-01-16 |
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r-ecmwfr
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public |
Programmatic interface to the European Centre for Medium-Range Weather Forecasts dataset web services (ECMWF; <https://www.ecmwf.int/>) and Copernicus's Climate Data Store (CDS; <https://cds.climate.copernicus.eu>). Allows for easy downloads of weather forecasts and climate reanalysis data in R.
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2024-01-16 |
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r-ecoreg
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public |
Estimating individual-level covariate-outcome associations using aggregate data ("ecological inference") or a combination of aggregate and individual-level data ("hierarchical related regression").
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2024-01-16 |
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r-econdemand
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public |
Tools for general properties including price, quantity, elasticity, convexity, marginal revenue and manifold of various economics demand systems including Linear, Translog, CES, LES and CREMR.
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2024-01-16 |
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r-ecohydmod
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public |
Simulates the soil water balance (soil moisture, evapotranspiration, leakage and runoff), rainfall series by using the marked Poisson process and the vegetation growth through the normalized difference vegetation index (NDVI). Please see Souza et al. (2016) <doi:10.1002/hyp.10953>.
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2024-01-16 |
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r-ecfun
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public |
Functions and vignettes to update data sets in 'Ecdat' and to create, manipulate, plot, and analyze those and similar data sets.
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2024-01-16 |
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r-echarts4r
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public |
Easily create interactive charts by leveraging the 'Echarts Javascript' library which includes 36 chart types, themes, 'Shiny' proxies and animations.
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2024-01-16 |
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r-ecdat
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public |
Data sets for econometrics, including political science.
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2024-01-16 |
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r-ecipex
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public |
Provides a function that quickly computes the fine structure isotope patterns of a set of chemical formulas to a given degree of accuracy (up to the limit set by errors in floating point arithmetic). A data-set comprising the masses and isotopic abundances of individual elements is also provided and calculation of isotopic gross structures is also supported.
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2024-01-16 |
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r-ecb
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public |
Provides an interface to the 'European Central Bank's Statistical Data Warehouse' API <https://sdw.ecb.europa.eu/>, allowing for programmatic retrieval of a vast quantity of statistical data.
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2024-01-16 |
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r-echarts2shiny
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public |
Embed interactive charts to their Shiny applications. These charts will be generated by ECharts library developed by Baidu (<http://echarts.baidu.com/>). Current version supports line chart, bar chart, pie chart, scatter plot, gauge, word cloud, radar chart, tree map, and heat map.
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2024-01-16 |
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r-easystats
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public |
A meta-package that installs and loads a set of packages from 'easystats' ecosystem in a single step. This collection of packages provide a unifying and consistent framework for statistical modeling, visualization, and reporting. Additionally, it provides articles targeted at instructors for teaching 'easystats', and a dashboard targeted at new R users for easily conducting statistical analysis by accessing summary results, model fit indices, and visualizations with minimal programming.
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2024-01-16 |
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r-ebayesthresh
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public |
Empirical Bayes thresholding using the methods developed by I. M. Johnstone and B. W. Silverman. The basic problem is to estimate a mean vector given a vector of observations of the mean vector plus white noise, taking advantage of possible sparsity in the mean vector. Within a Bayesian formulation, the elements of the mean vector are modelled as having, independently, a distribution that is a mixture of an atom of probability at zero and a suitable heavy-tailed distribution. The mixing parameter can be estimated by a marginal maximum likelihood approach. This leads to an adaptive thresholding approach on the original data. Extensions of the basic method, in particular to wavelet thresholding, are also implemented within the package.
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2024-01-16 |
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r-easypackages
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public |
Easily load and install multiple packages from different sources, including CRAN and GitHub. The libraries function allows you to load or attach multiple packages in the same function call. The packages function will load one or more packages, and install any packages that are not installed on your system (after prompting you). Also included is a from_import function that allows you to import specific functions from a package into the global environment.
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2024-01-16 |
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r-ebrank
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public |
Empirical Bayes ranking applicable to parallel-estimation settings where the estimated parameters are asymptotically unbiased and normal, with known standard errors. A mixture normal prior for each parameter is estimated using Empirical Bayes methods, subsequentially ranks for each parameter are simulated from the resulting joint posterior over all parameters (The marginal posterior densities for each parameter are assumed independent). Finally, experiments are ordered by expected posterior rank, although computations minimizing other plausible rank-loss functions are also given.
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2024-01-16 |
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r-ebprs
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public |
EB-PRS is a novel method that leverages information for effect sizes across all the markers to improve the prediction accuracy. No parameter tuning is needed in the method, and no external information is needed. This R-package provides the calculation of polygenic risk scores from the given training summary statistics and testing data. We can use EB-PRS to extract main information, estimate Empirical Bayes parameters, derive polygenic risk scores for each individual in testing data, and evaluate the PRS according to AUC and predictive r2. See Song et al. (2020) <doi:10.1371/journal.pcbi.1007565> for a detailed presentation of the method.
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2024-01-16 |
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r-ebgenotyping
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public |
Genotyping the population using next generation sequencing data is essentially important for the rare variant detection. In order to distinguish the genomic structural variation from sequencing error, we propose a statistical model which involves the genotype effect through a latent variable to depict the distribution of non-reference allele frequency data among different samples and different genome loci, while decomposing the sequencing error into sample effect and positional effect. An ECM algorithm is implemented to estimate the model parameters, and then the genotypes and SNPs are inferred based on the empirical Bayes method.
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2024-01-16 |
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r-ebal
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public |
Package implements entropy balancing, a data preprocessing procedure described in Hainmueller (2008, <doi:10.1093/pan/mpr025>) that allows users to reweight a dataset such that the covariate distributions in the reweighted data satisfy a set of user specified moment conditions. This can be useful to create balanced samples in observational studies with a binary treatment where the control group data can be reweighted to match the covariate moments in the treatment group. Entropy balancing can also be used to reweight a survey sample to known characteristics from a target population.
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2024-01-16 |
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r-easysvg
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public |
This SVG elements generator can easily generate SVG elements such as rect, line, circle, ellipse, polygon, polyline, text and group. Also, it can combine and output SVG elements into a SVG file.
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2024-01-16 |
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r-easyreg
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public |
Performs analysis of regression in simple designs with quantitative treatments, including mixed models and non linear models.
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2024-01-16 |
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r-easypubmed
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public |
Query NCBI Entrez and retrieve PubMed records in XML or text format. Process PubMed records by extracting and aggregating data from selected fields. A large number of records can be easily downloaded via this simple-to-use interface to the NCBI PubMed API.
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2024-01-16 |
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r-dynnom
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public |
Demonstrate the results of a statistical model object as a dynamic nomogram in an RStudio panel or web browser. The package provides two generics functions: DynNom, which display statistical model objects as a dynamic nomogram; DNbuilder, which builds required scripts to publish a dynamic nomogram on a web server such as the <https://www.shinyapps.io/>. Current version of 'DynNom' supports stats::lm, stats::glm, survival::coxph, rms::ols, rms::Glm, rms::lrm, rms::cph, mgcv::gam and gam::gam model objects.
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2024-01-16 |
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r-dynlm
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public |
Dynamic linear models and time series regression.
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2024-01-16 |
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r-dynetnlaresistance
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public |
An anonymization algorithm to resist neighbor label attack in a dynamic network.
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2024-01-16 |
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r-easynls
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public |
Fit and plot some nonlinear models.
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2024-01-16 |
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r-easycsv
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public |
Allows users to easily read multiple comma separated tables and create a data frame under the same name. Is able to read multiple comma separated tables from a local directory, a zip file or a zip file on a remote directory.
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2024-01-16 |
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r-easyanova
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public |
Perform analysis of variance and other important complementary analyses. The functions are easy to use. Performs analysis in various designs, with balanced and unbalanced data.
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2024-01-16 |
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r-easyahp
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public |
Given the scores from decision makers, the analytic hierarchy process can be conducted easily.
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2024-01-16 |
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r-dynprog
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public |
A domain-specific language for specifying translating recursions into dynamic-programming algorithms. See <https://en.wikipedia.org/wiki/Dynamic_programming> for a description of dynamic programming.
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2024-01-16 |
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r-dynpanel
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public |
Computes the first stage GMM estimate of a dynamic linear model with p lags of the dependent variables.
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2024-01-16 |
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r-dyncomp
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public |
While there are many well-established measures for identifying critical fluctuations and phase transitions, these measures only work with many points of measurement and thus are unreliable when studying short and coarse-grained time series. This package provides a measure for complexity in a time series that does not rely on long time series (Kaiser (2017), <doi:10.17605/OSF.IO/GWTKX>).
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2024-01-16 |
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r-dynamac
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public |
While autoregressive distributed lag (ARDL) models allow for extremely flexible dynamics, interpreting substantive significance of complex lag structures remains difficult. This package is designed to assist users in dynamically simulating and plotting the results of various ARDL models. It also contains post-estimation diagnostics, including a test for cointegration when estimating the error-correction variant of the autoregressive distributed lag model (Pesaran, Shin, and Smith 2001 <doi:10.1002/jae.616>).
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2024-01-16 |
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r-dynclust
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public |
A two-stage procedure for the denoising and clustering of stack of noisy images acquired over time. Clustering only assumes that the data contain an unknown but small number of dynamic features. The method first denoises the signals using local spatial and full temporal information. The clustering step uses the previous output to aggregate voxels based on the knowledge of their spatial neighborhood. Both steps use a single keytool based on the statistical comparison of the difference of two signals with the null signal. No assumption is therefore required on the shape of the signals. The data are assumed to be normally distributed (or at least follow a symmetric distribution) with a known constant variance. Working pixelwise, the method can be time-consuming depending on the size of the data-array but harnesses the power of multicore cpus.
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2024-01-16 |
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r-dyn
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public |
Time series regression. The dyn class interfaces ts, irts(), zoo() and zooreg() time series classes to lm(), glm(), loess(), quantreg::rq(), MASS::rlm(), MCMCpack::MCMCregress(), quantreg::rq(), randomForest::randomForest() and other regression functions allowing those functions to be used with time series including specifications that may contain lags, diffs and missing values.
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2024-01-16 |
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r-dynamictreecut
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public |
Contains methods for detection of clusters in hierarchical clustering dendrograms.
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2024-01-16 |
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r-dygraphs
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None |
An R interface to the 'dygraphs' JavaScript charting library (a copy of which is included in the package). Provides rich facilities for charting time-series data in R, including highly configurable series- and axis-display and interactive features like zoom/pan and series/point highlighting.
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2024-01-16 |
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r-dym
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public |
Add a "Did You Mean" feature to the R interactive. With this package, error messages for misspelled input of variable names or package names suggest what you really want to do in addition to notification of the mistake.
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2024-01-16 |
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r-dyads
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public |
Contains functions for the MCMC simulation of dyadic network models j2 (Zijlstra, 2017, <doi:10.1080/0022250X.2017.1387858>) and p2 (Van Duijn, Snijders & Zijlstra, 2004, <doi: 10.1046/j.0039-0402.2003.00258.x>), the multilevel p2 model (Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>), and the bidirectional (multilevel) counterpart of the the multilevel p2 model as described in Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>, the (multilevel) b2 model.
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2024-01-16 |
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r-dykstra
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public |
Solves quadratic programming problems using Richard L. Dykstra's cyclic projection algorithm. Routine allows for a combination of equality and inequality constraints. See Dykstra (1983) <doi:10.1080/01621459.1983.10477029> for details.
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2024-01-16 |
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r-dwlm
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public |
This linear model solution is useful when both predictor and response have associated uncertainty. The doubly weights linear model solution is invariant on which quantity is used as predictor or response. Based on the results by Reed(1989) <doi:10.1119/1.15963> and Ripley & Thompson(1987) <doi:10.1039/AN9871200377>.
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2024-01-16 |
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r-dydea
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public |
Finds regular and chaotic intervals in the data using the 0-1 test for chaos proposed by Gottwald and Melbourne (2004) <DOI:10.1137/080718851>.
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2024-01-16 |
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r-dwdlarger
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public |
Solving large scale distance weighted discrimination. The main algorithm is a symmetric Gauss-Seidel based alternating direction method of multipliers (ADMM) method. See Lam, X.Y., Marron, J.S., Sun, D.F., and Toh, K.C. (2018) <arXiv:1604.05473> for more details.
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2024-01-16 |
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r-dslabs
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public |
Datasets and functions that can be used for data analysis practice, homework and projects in data science courses and workshops. 26 datasets are available for case studies in data visualization, statistical inference, modeling, linear regression, data wrangling and machine learning.
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2024-01-16 |
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r-dunn.test
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Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.
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2024-01-16 |
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r-dummy
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public |
Efficiently create dummies of all factors and character vectors in a data frame. Support is included for learning the categories on one data set (e.g., a training set) and deploying them on another (e.g., a test set).
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2024-01-16 |
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r-dub
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public |
Provides an operator for assigning nested components of a list to names via a concise pattern matching syntax. This is especially convenient for assigning individual names to the multiple values that a function may return in the form of a list, and for extracting deeply nested list components.
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2024-01-16 |
