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r-effecttreat
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In personalized medicine, one wants to know, for a given patient and his or her outcome for a predictor (pre-treatment variable), how likely it is that a treatment will be more beneficial than an alternative treatment. This package allows for the quantification of the predictive causal association (i.e., the association between the predictor variable and the individual causal effect of the treatment) and related metrics. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
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2023-06-16 |
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r-envcpt
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Tools for automatic model selection and diagnostics for Climate and Environmental data. In particular the envcpt() function does automatic model selection between a variety of trend, changepoint and autocorrelation models. The envcpt() function should be your first port of call.
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2023-06-16 |
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r-eive
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Performs a compact genetic algorithm search to reduce errors-in-variables bias in linear regression. The algorithm estimates the regression parameters with lower biases and higher variances but mean-square errors (MSEs) are reduced.
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2023-06-16 |
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r-easynls
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Fit and plot some nonlinear models.
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2023-06-16 |
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r-dzexpm
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MCMC method to estimate and predict skewed spatial processes. A real data set is included. Reference: Wang, Yang and Majumdar (2018) <doi.org/10.1007/s00180-017-0741-3>.
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2023-06-16 |
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r-elmso
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An implementation of the algorithm described in "Efficient Large- Scale Internet Media Selection Optimization for Online Display Advertising" by Paulson, Luo, and James (Journal of Marketing Research 2018; see URL below for journal text/citation and <http://www-bcf.usc.edu/~gareth/research/ELMSO.pdf> for a full-text version of the paper). The algorithm here is designed to allocate budget across a set of online advertising opportunities using a coordinate-descent approach, but it can be used in any resource-allocation problem with a matrix of visitation (in the case of the paper, website page- views) and channels (in the paper, websites). The package contains allocation functions both in the presence of bidding, when allocation is dependent on channel-specific cost curves, and when advertising costs are fixed at each channel.
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2023-06-16 |
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r-elmr
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Training and prediction functions are provided for the Extreme Learning Machine algorithm (ELM). The ELM use a Single Hidden Layer Feedforward Neural Network (SLFN) with random generated weights and no gradient-based backpropagation. The training time is very short and the online version allows to update the model using small chunk of the training set at each iteration. The only parameter to tune is the hidden layer size and the learning function.
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2023-06-16 |
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r-elliplot
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Correlation chart of two set (x and y) of data. Using Quantiles. Visualize the effect of factor.
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2023-06-16 |
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r-elec
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This is a bizarre collection of functions written to do various sorts of statistical election audits. There are also functions to generate simulated voting data, and simulated "truth" so as to do simulations to check characteristics of these methods.
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2023-06-16 |
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r-elasticnet
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Provides functions for fitting the entire solution path of the Elastic-Net and also provides functions for estimating sparse Principal Components. The Lasso solution paths can be computed by the same function. First version: 2005-10.
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2023-06-16 |
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r-efflog
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Fitting a causal loglinear model and calculating the causal effects for a causal loglinear model with the multiplicative interaction or without the multiplicative interaction, obtaining the natural direct, indirect and the total effect. It calculates also the cell effect, which is a new interaction effect.
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2023-06-16 |
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r-edfun
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Easily creating empirical distribution functions from data: 'dfun', 'pfun', 'qfun' and 'rfun'.
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2023-06-16 |
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r-envipat
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Fast and very memory-efficient calculation of isotope patterns, subsequent convolution to theoretical envelopes (profiles) plus valley detection and centroidization or intensoid calculation. Batch processing, resolution interpolation, wrapper, adduct calculations and molecular formula parsing. Loos, M., Gerber, C., Corona, F., Hollender, J., Singer, H. (2015) <doi:10.1021/acs.analchem.5b00941>.
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2023-06-16 |
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r-enc
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Implements an S3 class for storing 'UTF-8' strings, based on regular character vectors. Also contains routines to portably read and write 'UTF-8' encoded text files, to convert all strings in an object to 'UTF-8', and to create character vectors with various encodings.
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2023-06-16 |
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r-emcdf
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Computes and visualizes empirical joint distribution of multivariate data with optimized algorithms and multi-thread computation. There is a faster algorithm using dynamic programming to compute the whole empirical joint distribution of a bivariate data. There are optimized algorithms for computing empirical joint CDF function values for other multivariate data. Visualization is focused on bivariate data. Levelplots and wireframes are included.
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2023-06-16 |
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r-ebrank
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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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2023-06-16 |
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r-easysvg
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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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2023-06-16 |
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r-easyreg
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Performs analysis of regression in simple designs with quantitative treatments, including mixed models and non linear models.
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2023-06-16 |
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r-dydea
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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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2023-06-16 |
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r-emmreml
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The main functions are 'emmreml', and 'emmremlMultiKernel'. 'emmreml' solves a mixed model with known covariance structure using the 'EMMA' algorithm. 'emmremlMultiKernel' is a wrapper for 'emmreml' to handle multiple random components with known covariance structures. The function 'emmremlMultivariate' solves a multivariate gaussian mixed model with known covariance structure using the 'ECM' algorithm.
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2023-06-16 |
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r-emdist
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Package providing calculation of Earth Mover's Distance (EMD).
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2023-06-16 |
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r-emcluster
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EM algorithms and several efficient initialization methods for model-based clustering of finite mixture Gaussian distribution with unstructured dispersion in both of unsupervised and semi-supervised learning.
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2023-06-16 |
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r-ecoreg
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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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2023-06-16 |
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r-easycsv
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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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2023-06-16 |
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r-dynamictreecut
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Contains methods for detection of clusters in hierarchical clustering dendrograms.
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2023-06-16 |
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r-dtables
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Towards automation of descriptive frequencies and statistics tables.
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2023-06-16 |
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r-bdots
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Analyze differences among time series curves with p-value adjustment for multiple comparisons introduced in Oleson et al (2015) <DOI:10.1177/0962280215607411>.
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2023-06-16 |
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r-ande
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AODE achieves highly accurate classification by averaging over all of a small space.
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2023-06-16 |
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r-ems
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Collection of functions for data analysis and editing of clinical and epidemiological data. Most of them are related to benchmark with prediction models.
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2023-06-16 |
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r-emhawkes
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Simulate and fitting exponential multivariate Hawkes model. This package simulates a multivariate Hawkes model, introduced by Hawkes (1971) <doi:10.1093/biomet/58.1.83>, with an exponential kernel and fits the parameters from the data. Models with the constant parameters, as well as complex dependent structures, can also be simulated and estimated. The estimation is based on the maximum likelihood method, introduced by introduced by Ozaki (1979) <doi:10.1007/BF02480272>, with 'maxLik' package.
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2023-06-16 |
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r-elexr
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Provides R access to election results data. Wraps elex (https://github.com/newsdev/elex/), a Python package and command line tool for fetching and parsing Associated Press election results.
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2023-06-16 |
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r-eigenmodel
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Estimation of the parameters in a model for symmetric relational data (e.g., the above-diagonal part of a square matrix), using a model-based eigenvalue decomposition and regression. Missing data is accommodated, and a posterior mean for missing data is calculated under the assumption that the data are missing at random. The marginal distribution of the relational data can be arbitrary, and is fit with an ordered probit specification. See Hoff (2007) <arXiv:0711.1146> for details on the model.
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2023-06-16 |
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r-effectstars2
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Provides functions for the method of effect stars as proposed by Tutz and Schauberger (2013) <doi:10.1080/10618600.2012.701379>. Effect stars can be used to visualize estimates of parameters corresponding to different groups, for example in multinomial logit models. Beside the main function 'effectstars' there exist methods for special objects, for example for 'vglm' objects from the 'VGAM' package.
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2023-06-16 |
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r-dyads
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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>) as described in Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>.
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2023-06-16 |
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r-emulator
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Allows one to estimate the output of a computer program, as a function of the input parameters, without actually running it. The computer program is assumed to be a Gaussian process, whose parameters are estimated using Bayesian techniques that give a PDF of expected program output. This PDF is conditional on a training set of runs, each consisting of a point in parameter space and the model output at that point. The emphasis is on complex codes that take weeks or months to run, and that have a large number of undetermined input parameters; many climate prediction models fall into this class. The emulator essentially determines Bayesian posterior estimates of the PDF of the output of a model, conditioned on results from previous runs and a user-specified prior linear model. A vignette is provided and the help pages include examples.
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2023-06-16 |
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r-emistatr
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Provides a fast and parallelised calculator to estimate combined wastewater emissions. It supports the planning and design of urban drainage systems, without the requirement of extensive simulation tools. The 'EmiStatR' package implements modular R methods. This enables to add new functionalities through the R framework.
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2023-06-16 |
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r-emg
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Provides basic distribution functions for a mixture model of a Gaussian and exponential distribution.
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2023-06-16 |
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r-effectstars
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Notice: The package EffectStars2 provides a more up-to-date implementation of effect stars! EffectStars provides functions to visualize regression models with categorical response as proposed by Tutz and Schauberger (2013) <doi:10.1080/10618600.2012.701379>. The effects of the variables are plotted with star plots in order to allow for an optical impression of the fitted model.
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2023-06-16 |
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r-emc
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random walk Metropolis, Metropolis Hasting, parallel tempering, evolutionary Monte Carlo, temperature ladder construction and placement
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2023-06-16 |
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r-edf
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Import physiologic data stored in the European Data Format (EDF and EDF+) into R. Both EDF and EDF+ files are supported. Discontinuous EDF+ files are not yet supported.
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2023-06-16 |
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r-ebprs
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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.
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2023-06-16 |
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r-easypubmed
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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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2023-06-16 |
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r-dyn
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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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2023-06-16 |
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r-endogenous
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Likelihood-based approaches to estimate linear regression parameters and treatment effects in the presence of endogeneity. Specifically, this package includes James Heckman's classical simultaneous equation models-the sample selection model for outcome selection bias and hybrid model with structural shift for endogenous treatment. For more information, see the seminal paper of Heckman (1978) <DOI:10.3386/w0177> in which the details of these models are provided. This package accommodates repeated measures on subjects with a working independence approach. The hybrid model further accommodates treatment effect modification.
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2023-06-16 |
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r-eegkitdata
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Contains the example EEG data used in the package eegkit. Also contains code for easily creating larger EEG datasets from the EEG Database on the UCI Machine Learning Repository.
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2023-06-16 |
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r-eha
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Sampling of risk sets in Cox regression, selections in the Lexis diagram, bootstrapping. Parametric proportional hazards fitting with left truncation and right censoring for common families of distributions, piecewise constant hazards, and discrete models. Parametric accelerated failure time models for left truncated and right censored data.
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2023-06-16 |
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r-emvs
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An efficient expectation-maximization algorithm for fitting Bayesian spike-and-slab regularization paths for linear regression. Rockova and George (2014) <doi:10.1080/01621459.2013.869223>.
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2023-06-16 |
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r-emmixmfa
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We provide functions to fit finite mixtures of multivariate normal or t-distributions to data with various factor analytic structures adopted for the covariance/scale matrices. The factor analytic structures available include mixtures of factor analyzers and mixtures of common factor analyzers. The latter approach is so termed because the matrix of factor loadings is common to components before the component-specific rotation of the component factors to make them white noise. Note that the component-factor loadings are not common after this rotation. Maximum likelihood estimators of model parameters are obtained via the Expectation-Maximization algorithm. See descriptions of the algorithms used in McLachlan GJ, Peel D (2000) <doi:10.1002/0471721182.ch8> McLachlan GJ, Peel D (2000) <ISBN:1-55860-707-2> McLachlan GJ, Peel D, Bean RW (2003) <doi:10.1016/S0167-9473(02)00183-4> McLachlan GJ, Bean RW, Ben-Tovim Jones L (2007) <doi:10.1016/j.csda.2006.09.015> Baek J, McLachlan GJ, Flack LK (2010) <doi:10.1109/TPAMI.2009.149> Baek J, McLachlan GJ (2011) <doi:10.1093/bioinformatics/btr112> McLachlan GJ, Baek J, Rathnayake SI (2011) <doi:10.1002/9781119995678.ch9>.
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2023-06-16 |
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r-ecohydmod
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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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2023-06-16 |
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r-dynetnlaresistance
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An anonymization algorithm to resist neighbor label attack in a dynamic network.
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2023-06-16 |
