revdbayes - Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
Provides functions for the Bayesian analysis of extreme value models. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution. The functionality of 'revdbayes' is similar to the 'evdbayes' package <https://cran.r-project.org/package=evdbayes>, which uses Markov Chain Monte Carlo ('MCMC') methods for posterior simulation. In addition, there are functions for making inferences about the extremal index, using the models for threshold inter-exceedance times of Suveges and Davison (2010) <doi:10.1214/09-AOAS292> and Holesovsky and Fusek (2020) <doi:10.1007/s10687-020-00374-3>. Also provided are d,p,q,r functions for the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') distributions that deal appropriately with cases where the shape parameter is very close to zero.
Last updated 3 months ago
analysisbayesianextremeextreme-value-statisticsextremesgeneralized-pareto-distributiongevinferencenhpppoint-processposteriorpredictivercppvalue
7.83 score 4 stars 4 packages 58 scripts 1.7k downloadsfExtremes - Rmetrics - Modelling Extreme Events in Finance
Provides functions for analysing and modelling extreme events in financial time Series. The topics include: (i) data pre-processing, (ii) explorative data analysis, (iii) peak over threshold modelling, (iv) block maxima modelling, (v) estimation of VaR and CVaR, and (vi) the computation of the extreme index.
Last updated 2 days ago
7.50 score 1 stars 4 packages 119 scripts 1.4k downloadsrust - Ratio-of-Uniforms Simulation with Transformation
Uses the generalized ratio-of-uniforms (RU) method to simulate from univariate and (low-dimensional) multivariate continuous distributions. The user specifies the log-density, up to an additive constant. The RU algorithm is applied after relocation of mode of the density to zero, and the user can choose a tuning parameter r. For details see Wakefield, Gelfand and Smith (1991) <DOI:10.1007/BF01889987>, Efficient generation of random variates via the ratio-of-uniforms method, Statistics and Computing (1991) 1, 129-133. A Box-Cox variable transformation can be used to make the input density suitable for the RU method and to improve efficiency. In the multivariate case rotation of axes can also be used to improve efficiency. From version 1.2.0 the 'Rcpp' package <https://cran.r-project.org/package=Rcpp> can be used to improve efficiency.
Last updated 3 months ago
1977bayesian-inferencekindermanmonahanofposterior-samplesratioratio-of-uniformsratio-of-uniforms-methodrcppsimulationtransformationuniformsopenblascpp
7.23 score 7 packages 36 scripts 808 downloadschandwich - Chandler-Bate Sandwich Loglikelihood Adjustment
Performs adjustments of a user-supplied independence loglikelihood function using a robust sandwich estimator of the parameter covariance matrix, based on the methodology in Chandler and Bate (2007) <doi:10.1093/biomet/asm015>. This can be used for cluster correlated data when interest lies in the parameters of the marginal distributions or for performing inferences that are robust to certain types of model misspecification. Functions for profiling the adjusted loglikelihoods are also provided, as are functions for calculating and plotting confidence intervals, for single model parameters, and confidence regions, for pairs of model parameters. Nested models can be compared using an adjusted likelihood ratio test.
Last updated 1 years ago
clustered-dataclusterscomposite-likelihoodindependence-loglikelihoodmlerobustsandwichstatistical-inference
5.88 score 4 stars 7 packages 18 scripts 608 downloadsthreshr - Threshold Selection and Uncertainty for Extreme Value Analysis
Provides functions for the selection of thresholds for use in extreme value models, based mainly on the methodology in Northrop, Attalides and Jonathan (2017) <doi:10.1111/rssc.12159>. It also performs predictive inferences about future extreme values, based either on a single threshold or on a weighted average of inferences from multiple thresholds, using the 'revdbayes' package <https://cran.r-project.org/package=revdbayes>. At the moment only the case where the data can be treated as independent identically distributed observations is considered.
Last updated 4 months ago
extreme-value-statisticsextremesgeneralizedinferenceparetoplotpredictionthresholdthreshold-selectionuncertainty
5.75 score 6 stars 1 packages 31 scripts 311 downloadsbang - Bayesian Analysis, No Gibbs
Provides functions for the Bayesian analysis of some simple commonly-used models, without using Markov Chain Monte Carlo (MCMC) methods such as Gibbs sampling. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution, using the generalized ratio-of-uniforms method. See Wakefield, Gelfand and Smith (1991) <DOI:10.1007/BF01889987> for details. At the moment three conjugate hierarchical models are available: beta-binomial, gamma-Poisson and a 1-way analysis of variance (ANOVA).
Last updated 4 months ago
anovabayesianbetabinomialgammagibbshierarchicalpoisson
5.62 score 3 stars 35 scripts 881 downloadsfRegression - Rmetrics - Regression Based Decision and Prediction
A collection of functions for linear and non-linear regression modelling. It implements a wrapper for several regression models available in the base and contributed packages of R.
Last updated 2 days ago
5.55 score 1 stars 23 scripts 543 downloadsexdex - Estimation of the Extremal Index
Performs frequentist inference for the extremal index of a stationary time series. Two types of methodology are used. One type is based on a model that relates the distribution of block maxima to the marginal distribution of series and leads to the semiparametric maxima estimators described in Northrop (2015) <doi:10.1007/s10687-015-0221-5> and Berghaus and Bucher (2018) <doi:10.1214/17-AOS1621>. Sliding block maxima are used to increase precision of estimation. A graphical block size diagnostic is provided. The other type of methodology uses a model for the distribution of threshold inter-exceedance times (Ferro and Segers (2003) <doi:10.1111/1467-9868.00401>). Three versions of this type of approach are provided: the iterated weight least squares approach of Suveges (2007) <doi:10.1007/s10687-007-0034-2>, the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292> and a similar approach of Holesovsky and Fusek (2020) <doi:10.1007/s10687-020-00374-3> that we refer to as D-gaps. For the K-gaps and D-gaps models this package allows missing values in the data, can accommodate independent subsets of data, such as monthly or seasonal time series from different years, and can incorporate information from right-censored inter-exceedance times. Graphical diagnostics for the threshold level and the respective tuning parameters K and D are provided.
Last updated 7 months ago
block-maximaextremal-indexextremeextreme-value-statisticsextremesinferencemaximasemiparametricsemiparametric-estimationsemiparametric-maxima-estimatorsthetathresholdvalue
5.22 score 5 packages 11 scripts 606 downloadsitp - The Interpolate, Truncate, Project (ITP) Root-Finding Algorithm
Implements the Interpolate, Truncate, Project (ITP) root-finding algorithm developed by Oliveira and Takahashi (2021) <doi:10.1145/3423597>. The user provides the function, from the real numbers to the real numbers, and an interval with the property that the values of the function at its endpoints have different signs. If the function is continuous over this interval then the ITP method estimates the value at which the function is equal to zero. If the function is discontinuous then a point of discontinuity at which the function changes sign may be found. The function can be supplied using either an R function or an external pointer to a C++ function. Tuning parameters of the ITP algorithm can be set by the user. Default values are set based on arguments in Oliveira and Takahashi (2021).
Last updated 6 months ago
algorithmbracketingitpitp-methodroot-finding
5.13 score 9 stars 8 scripts 229 downloadslax - Loglikelihood Adjustment for Extreme Value Models
Performs adjusted inferences based on model objects fitted, using maximum likelihood estimation, by the extreme value analysis packages 'eva' <https://cran.r-project.org/package=eva>, 'evd' <https://cran.r-project.org/package=evd>, 'evir' <https://cran.r-project.org/package=evir>, 'extRemes' <https://cran.r-project.org/package=extRemes>, 'fExtremes' <https://cran.r-project.org/package=fExtremes>, 'ismev' <https://cran.r-project.org/package=ismev>, 'mev' <https://cran.r-project.org/package=mev>, 'POT' <https://cran.r-project.org/package=POT> and 'texmex' <https://cran.r-project.org/package=texmex>. Adjusted standard errors and an adjusted loglikelihood are provided, using the 'chandwich' package <https://cran.r-project.org/package=chandwich> and the object-oriented features of the 'sandwich' package <https://cran.r-project.org/package=sandwich>. The adjustment is based on a robust sandwich estimator of the parameter covariance matrix, based on the methodology in Chandler and Bate (2007) <doi:10.1093/biomet/asm015>. This can be used for cluster correlated data when interest lies in the parameters of the marginal distributions, or for performing inferences that are robust to certain types of model misspecification. Univariate extreme value models, including regression models, are supported.
Last updated 9 months ago
clustered-dataclusterscomposite-likelihoodevdextreme-value-analysisextreme-value-statisticsextremesindependence-loglikelihoodloglikelihood-adjustmentmlepotregressionregression-modellingrobustsandwichsandwich-estimator
4.59 score 3 stars 13 scripts 283 downloadslite - Likelihood-Based Inference for Time Series Extremes
Performs likelihood-based inference for stationary time series extremes. The general approach follows Fawcett and Walshaw (2012) <doi:10.1002/env.2133>. Marginal extreme value inferences are adjusted for cluster dependence in the data using the methodology in Chandler and Bate (2007) <doi:10.1093/biomet/asm015>, producing an adjusted log-likelihood for the model parameters. A log-likelihood for the extremal index is produced using the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. These log-likelihoods are combined to make inferences about extreme values. Both maximum likelihood and Bayesian approaches are available.
Last updated 4 months ago
clusteredextremal-indexextreme-value-statisticsextremesfrequentistgeneralised-paretoinferencelikelihoodlog-likelihoodthresholdtime-series
4.56 score 3 stars 12 scripts 222 downloadsdonut - Nearest Neighbour Search with Variables on a Torus
Finds the k nearest neighbours in a dataset of specified points, adding the option to wrap certain variables on a torus. The user chooses the algorithm to use to find the nearest neighbours. Two such algorithms, provided by the packages 'RANN' <https://cran.r-project.org/package=RANN>, and 'nabor' <https://cran.r-project.org/package=nabor>, are suggested.
Last updated 1 years ago
degreesdonutedgesknn-algorithmknn-searchnabornearestnearest-neighbornearest-neighbor-searchnearest-neighborsnearest-neighbour-algorithmnearest-neighboursneighborsperiodicityranntoruswrap
4.18 score 1 stars 1 packages 5 scripts 491 downloadsgamlssx - Generalized Additive Extreme Value Models for Location, Scale and Shape
Fits generalized additive models for the location, scale and shape parameters of a generalized extreme value response distribution. The methodology is based on Rigby, R.A. and Stasinopoulos, D.M. (2005), <doi:10.1111/j.1467-9876.2005.00510.x> and implemented using functions from the 'gamlss' package <doi:10.32614/CRAN.package.gamlss>.
Last updated 4 months ago
extreme-value-statisticsextremesgeneralized-additive-modelsregressionregression-analysis
3.90 score 2 stars 3 scripts 171 downloadsaccessr - Command Line Tools to Produce Accessible Documents using 'R Markdown'
Provides functions to produce accessible 'HTML' slides, 'HTML', 'Word' and 'PDF' documents from input 'R markdown' files. Accessible 'PDF' files are produced only on a 'Windows' Operating System. One aspect of accessibility is providing a headings structure that is recognised by a screen reader, providing a navigational tool for a blind or partially-sighted person. A key aim is to produce documents of different formats easily from each of a collection of 'R markdown' source files. Input 'R markdown' files are rendered using the render() function from the 'rmarkdown' package <https://cran.r-project.org/package=rmarkdown>. A 'zip' file containing multiple output files can be produced from one function call. A user-supplied template 'Word' document can be used to determine the formatting of an output 'Word' document. Accessible 'PDF' files are produced from 'Word' documents using 'OfficeToPDF' <https://github.com/cognidox/OfficeToPDF>. A convenience function, install_otp() is provided to install this software. The option to print 'HTML' output to (non-accessible) 'PDF' files is also available.
Last updated 6 months ago
accessibilitycommand-linedigital-accessibilityrmarkdownrmarkdown-documentrmarkdown-slide
3.70 score 1 scripts 551 downloadssmovie - Some Movies to Illustrate Concepts in Statistics
Provides movies to help students to understand statistical concepts. The 'rpanel' package <https://cran.r-project.org/package=rpanel> is used to create interactive plots that move to illustrate key statistical ideas and methods. There are movies to: visualise probability distributions (including user-supplied ones); illustrate sampling distributions of the sample mean (central limit theorem), the median, the sample maximum (extremal types theorem) and (the Fisher transformation of the) product moment correlation coefficient; examine the influence of an individual observation in simple linear regression; illustrate key concepts in statistical hypothesis testing. Also provided are dpqr functions for the distribution of the Fisher transformation of the correlation coefficient under sampling from a bivariate normal distribution.
Last updated 12 months ago
central-limit-theoremcorrelation-coefficientextremal-types-theoremextremeshypothesis-testinglikelihood-ratio-testlinear-regressionlog-likelihoodmovieprobability-distributionsregressionscore-teststatistical-conceptsstatisticsstatistics-learningteachingteaching-materialstest-statisticwald-test
3.70 score 1 stars 10 scripts 265 downloads