R-universe search: elliptic

robinhankin

elliptic:Weierstrass and Jacobi Elliptic Functions

A suite of elliptic and related functions including Weierstrass and Jacobi forms. Also includes various tools for manipulating and visualizing complex functions.

Maintained by Robin K. S. Hankin. Last updated 12 days ago.

64.3 match 3 stars 9.31 score 54 scripts 79 dependents

alexisderumigny

ElliptCopulas:Inference of Elliptical Distributions and Copulas

Provides functions for the simulation and the nonparametric estimation of elliptical distributions, meta-elliptical copulas and trans-elliptical distributions, following the article Derumigny and Fermanian (2022) <doi:10.1016/j.jmva.2022.104962>.

Maintained by Alexis Derumigny. Last updated 6 months ago.

copula elliptical-copula elliptical-distribution r-pkg

38.8 match 4 stars 4.38 score 2 scripts 1 dependents

jfrench

smerc:Statistical Methods for Regional Counts

Implements statistical methods for analyzing the counts of areal data, with a focus on the detection of spatial clusters and clustering. The package has a heavy emphasis on spatial scan methods, which were first introduced by Kulldorff and Nagarwalla (1995) <doi:10.1002/sim.4780140809> and Kulldorff (1997) <doi:10.1080/03610929708831995>.

Maintained by Joshua French. Last updated 5 months ago.

cpp

22.7 match 3 stars 6.11 score 45 scripts 3 dependents

stla

Carlson:Carlson Elliptic Integrals and Incomplete Elliptic Integrals

Evaluation of the Carlson elliptic integrals and the incomplete elliptic integrals with complex arguments. The implementations use Carlson's algorithms <doi:10.1007/BF02198293>. Applications of elliptic integrals include probability distributions, geometry, physics, mechanics, electrodynamics, statistical mechanics, astronomy, geodesy, geodesics on conics, and magnetic field calculations.

Maintained by Stéphane Laurent. Last updated 1 years ago.

elliptic-integrals special-functions cpp

28.2 match 1 stars 3.26 score 12 scripts 1 dependents

stla

jacobi:Jacobi Theta Functions and Related Functions

Evaluation of the Jacobi theta functions and related functions: Weierstrass elliptic function, Weierstrass sigma function, Weierstrass zeta function, Klein j-function, Dedekind eta function, lambda modular function, Jacobi elliptic functions, Neville theta functions, Eisenstein series, lemniscate elliptic functions, elliptic alpha function, Rogers-Ramanujan continued fractions, and Dixon elliptic functions. Complex values of the variable are supported.

Maintained by Stéphane Laurent. Last updated 1 years ago.

elliptic-functions theta-functions cpp

20.7 match 2 stars 4.01 score 103 scripts

r-forge

copula:Multivariate Dependence with Copulas

Classes (S4) of commonly used elliptical, Archimedean, extreme-value and other copula families, as well as their rotations, mixtures and asymmetrizations. Nested Archimedean copulas, related tools and special functions. Methods for density, distribution, random number generation, bivariate dependence measures, Rosenblatt transform, Kendall distribution function, perspective and contour plots. Fitting of copula models with potentially partly fixed parameters, including standard errors. Serial independence tests, copula specification tests (independence, exchangeability, radial symmetry, extreme-value dependence, goodness-of-fit) and model selection based on cross-validation. Empirical copula, smoothed versions, and non-parametric estimators of the Pickands dependence function.

Maintained by Martin Maechler. Last updated 12 days ago.

5.9 match 11.83 score 1.2k scripts 86 dependents

cran

sn:The Skew-Normal and Related Distributions Such as the Skew-t and the SUN

Build and manipulate probability distributions of the skew-normal family and some related ones, notably the skew-t and the SUN families. For the skew-normal and the skew-t distributions, statistical methods are provided for data fitting and model diagnostics, in the univariate and the multivariate case.

Maintained by Adelchi Azzalini. Last updated 2 years ago.

8.8 match 3 stars 7.44 score 92 dependents

gjmvanboxtel

gsignal:Signal Processing

R implementation of the 'Octave' package 'signal', containing a variety of signal processing tools, such as signal generation and measurement, correlation and convolution, filtering, filter design, filter analysis and conversion, power spectrum analysis, system identification, decimation and sample rate change, and windowing.

Maintained by Geert van Boxtel. Last updated 2 months ago.

signal-processing signals cpp

5.8 match 24 stars 10.03 score 133 scripts 34 dependents

robinhankin

gsl:Wrapper for the Gnu Scientific Library

An R wrapper for some of the functionality of the Gnu Scientific Library.

Maintained by Robin K. S. Hankin. Last updated 2 months ago.

gsl

4.5 match 15 stars 11.82 score 472 scripts 204 dependents

emanuelhuber

RConics:Computations on Conics

Solve some conic related problems (intersection of conics with lines and conics, arc length of an ellipse, polar lines, etc.).

Maintained by Emanuel Huber. Last updated 27 days ago.

conics ellipse elliptic geometry intersection

12.0 match 4.20 score 53 scripts 2 dependents

hwborchers

pracma:Practical Numerical Math Functions

Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.

Maintained by Hans W. Borchers. Last updated 1 years ago.

3.4 match 29 stars 12.34 score 6.6k scripts 931 dependents

mohsentaherishalmani

ETRep:Analysis of Elliptical Tubes Under the Relative Curvature Condition

Analysis of elliptical tubes with applications in biological modeling. The package is based on the references: Taheri, M., Pizer, S. M., & Schulz, J. (2024) "The Mean Shape under the Relative Curvature Condition." arXiv <doi:10.48550/arXiv.2404.01043>. Mohsen Taheri Shalmani (2024) "Shape Statistics via Skeletal Structures", PhD Thesis, University of Stavanger, Norway <doi:10.13140/RG.2.2.34500.23685>. Key features include constructing discrete elliptical tubes, calculating transformations, validating structures under the Relative Curvature Condition (RCC), computing means, and generating simulations. Supports intrinsic and non-intrinsic mean calculations and transformations, size estimation, plotting, and random sample generation based on a reference tube. The intrinsic approach relies on the interior path of the original non-convex space, incorporating the RCC, while the non-intrinsic approach uses a basic robotic arm transformation that disregards the RCC.

Maintained by Mohsen Taheri Shalmani. Last updated 2 months ago.

11.0 match 3.54 score 3 scripts

r-forge

signal:Signal Processing

A set of signal processing functions originally written for 'Matlab' and 'Octave'. Includes filter generation utilities, filtering functions, resampling routines, and visualization of filter models. It also includes interpolation functions.

Maintained by Uwe Ligges. Last updated 1 years ago.

fortran

3.9 match 8.78 score 828 scripts 151 dependents

tyy20

KEPTED:Kernel-Embedding-of-Probability Test for Elliptical Distribution

Provides an implementation of a kernel-embedding of probability test for elliptical distribution. This is an asymptotic test for elliptical distribution under general alternatives, and the location and shape parameters are assumed to be unknown. Some side-products are posted, including the transformation between rectangular and polar coordinates and two product-type kernel functions. See Tang and Li (2024) <doi:10.48550/arXiv.2306.10594> for details.

Maintained by Yin Tang. Last updated 11 months ago.

7.8 match 4.18 score

r-forge

distrEllipse:S4 Classes for Elliptically Contoured Distributions

Distribution (S4-)classes for elliptically contoured distributions (based on package 'distr').

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

9.3 match 3.51 score 18 scripts

andrisignorell

DescTools:Tools for Descriptive Statistics

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.

Maintained by Andri Signorell. Last updated 18 hours ago.

fortran cpp

1.9 match 87 stars 16.70 score 7.7k scripts 99 dependents

nepem-ufsc

pliman:Tools for Plant Image Analysis

Tools for both single and batch image manipulation and analysis (Olivoto, 2022 <doi:10.1111/2041-210X.13803>) and phytopathometry (Olivoto et al., 2022 <doi:10.1007/S40858-021-00487-5>). The tools can be used for the quantification of leaf area, object counting, extraction of image indexes, shape measurement, object landmark identification, and Elliptical Fourier Analysis of object outlines (Claude (2008) <doi:10.1007/978-0-387-77789-4>). The package also provides a comprehensive pipeline for generating shapefiles with complex layouts and supports high-throughput phenotyping of RGB, multispectral, and hyperspectral orthomosaics. This functionality facilitates field phenotyping using UAV- or satellite-based imagery.

Maintained by Tiago Olivoto. Last updated 5 hours ago.

openblas fftw3 cpp openmp

4.4 match 10 stars 6.70 score 476 scripts

katherineloor

relliptical:The Truncated Elliptical Family of Distributions

It offers random numbers generation from members of the truncated multivariate elliptical family of distribution such as the truncated versions of the Normal, Student-t, Laplace, Pearson VII, Slash, Logistic, among others. Particular distributions can be provided by specifying the density generating function. It also computes the first two moments (covariance matrix as well) for some particular distributions. References used for this package: Galarza, C. E., Matos, L. A., Castro, L. M., and Lachos, V. H. (2022). Moments of the doubly truncated selection elliptical distributions with emphasis on the unified multivariate skew-t distribution. Journal of Multivariate Analysis, 189, 104944 <doi:10.1016/j.jmva.2021.104944>; Ho, H. J., Lin, T. I., Chen, H. Y., and Wang, W. L. (2012). Some results on the truncated multivariate t distribution. Journal of Statistical Planning and Inference, 142(1), 25-40 <doi:10.1016/j.jspi.2011.06.006>; Valeriano, K. A., Galarza, C. E., and Matos, L. A. (2021). Moments and random number generation for the truncated elliptical family of distributions. Statistics and Computing, 33(1), 32 <doi:10.1007/s11222-022-10200-4>.

Maintained by Katherine A. L. Valeriano. Last updated 10 months ago.

openblas cpp openmp

7.5 match 3.88 score 5 scripts 5 dependents

martin3141

spant:MR Spectroscopy Analysis Tools

Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.

Maintained by Martin Wilson. Last updated 1 months ago.

brain mri mrs mrshub spectroscopy fortran

3.4 match 25 stars 8.52 score 81 scripts

momx

Momocs:Morphometrics using R

The goal of 'Momocs' is to provide a complete, convenient, reproducible and open-source toolkit for 2D morphometrics. It includes most common 2D morphometrics approaches on outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. It allows reproducible, complex morphometrics analyses and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.

Maintained by Vincent Bonhomme. Last updated 1 years ago.

morphometrics

3.8 match 51 stars 7.42 score 346 scripts

spatstat

spatstat.geom:Geometrical Functionality of the 'spatstat' Family

Defines spatial data types and supports geometrical operations on them. Data types include point patterns, windows (domains), pixel images, line segment patterns, tessellations and hyperframes. Capabilities include creation and manipulation of data (using command line or graphical interaction), plotting, geometrical operations (rotation, shift, rescale, affine transformation), convex hull, discretisation and pixellation, Dirichlet tessellation, Delaunay triangulation, pairwise distances, nearest-neighbour distances, distance transform, morphological operations (erosion, dilation, closing, opening), quadrat counting, geometrical measurement, geometrical covariance, colour maps, calculus on spatial domains, Gaussian blur, level sets of images, transects of images, intersections between objects, minimum distance matching. (Excludes spatial data on a network, which are supported by the package 'spatstat.linnet'.)

Maintained by Adrian Baddeley. Last updated 2 days ago.

classes-and-objects distance-calculation geometry geometry-processing images mensuration plotting point-patterns spatial-data spatial-data-analysis

2.3 match 7 stars 12.11 score 241 scripts 227 dependents

mlysy

nicheROVER:Niche Region and Niche Overlap Metrics for Multidimensional Ecological Niches

Implementation of a probabilistic method to calculate 'nicheROVER' (_niche_ _r_egion and niche _over_lap) metrics using multidimensional niche indicator data (e.g., stable isotopes, environmental variables, etc.). The niche region is defined as the joint probability density function of the multidimensional niche indicators at a user-defined probability alpha (e.g., 95%). Uncertainty is accounted for in a Bayesian framework, and the method can be extended to three or more indicator dimensions. It provides directional estimates of niche overlap, accounts for species-specific distributions in multivariate niche space, and produces unique and consistent bivariate projections of the multivariate niche region. The article by Swanson et al. (2015) <doi:10.1890/14-0235.1> provides a detailed description of the methodology. See the package vignette for a worked example using fish stable isotope data.

Maintained by Martin Lysy. Last updated 1 years ago.

3.6 match 9 stars 6.80 score 47 scripts 1 dependents

swihart

growth:Multivariate Normal and Elliptically-Contoured Repeated Measurements Models

Functions for fitting various normal theory (growth curve) and elliptically-contoured repeated measurements models with ARMA and random effects dependence.

Maintained by Bruce Swihart. Last updated 6 years ago.

fortran

8.0 match 3.00 score 6 scripts

dsy109

mixtools:Tools for Analyzing Finite Mixture Models

Analyzes finite mixture models for various parametric and semiparametric settings. This includes mixtures of parametric distributions (normal, multivariate normal, multinomial, gamma), various Reliability Mixture Models (RMMs), mixtures-of-regressions settings (linear regression, logistic regression, Poisson regression, linear regression with changepoints, predictor-dependent mixing proportions, random effects regressions, hierarchical mixtures-of-experts), and tools for selecting the number of components (bootstrapping the likelihood ratio test statistic, mixturegrams, and model selection criteria). Bayesian estimation of mixtures-of-linear-regressions models is available as well as a novel data depth method for obtaining credible bands. This package is based upon work supported by the National Science Foundation under Grant No. SES-0518772 and the Chan Zuckerberg Initiative: Essential Open Source Software for Science (Grant No. 2020-255193).

Maintained by Derek Young. Last updated 9 months ago.

mixture-models mixture-of-experts semiparametric-regression

2.0 match 20 stars 11.34 score 1.4k scripts 56 dependents

convexfi

fitHeavyTail:Mean and Covariance Matrix Estimation under Heavy Tails

Robust estimation methods for the mean vector, scatter matrix, and covariance matrix (if it exists) from data (possibly containing NAs) under multivariate heavy-tailed distributions such as angular Gaussian (via Tyler's method), Cauchy, and Student's t distributions. Additionally, a factor model structure can be specified for the covariance matrix. The latest revision also includes the multivariate skewed t distribution. The package is based on the papers: Sun, Babu, and Palomar (2014); Sun, Babu, and Palomar (2015); Liu and Rubin (1995); Zhou, Liu, Kumar, and Palomar (2019); Pascal, Ollila, and Palomar (2021).

Maintained by Daniel P. Palomar. Last updated 2 years ago.

cauchy covariance-estimation covariance-matrix heavy-tailed-distributions outliers robust-estimation student-t tyler

3.3 match 22 stars 6.27 score 28 scripts 1 dependents

vbaliga

gaussplotR:Fit, Predict and Plot 2D Gaussians

Functions to fit two-dimensional Gaussian functions, predict values from fits, and produce plots of predicted data via either 'ggplot2' or base R plotting.

Maintained by Vikram B. Baliga. Last updated 4 years ago.

2d-gaussian gaussian gaussian-fit gaussian-interpolation gaussian-plot gaussian-volume plotting

4.0 match 4 stars 5.10 score 21 scripts

ropensci

GLMMcosinor:Fit a Cosinor Model Using a Generalized Mixed Modeling Framework

Allows users to fit a cosinor model using the 'glmmTMB' framework. This extends on existing cosinor modeling packages, including 'cosinor' and 'circacompare', by including a wide range of available link functions and the capability to fit mixed models. The cosinor model is described by Cornelissen (2014) <doi:10.1186/1742-4682-11-16>.

Maintained by Rex Parsons. Last updated 4 months ago.

3.5 match 1 stars 5.77 score 22 scripts

mahditeimouri

alphastable:Inference for Stable Distribution

Developed to perform the tasks given by the following. 1-computing the probability density function and distribution function of a univariate stable distribution; 2- generating from univariate stable, truncated stable, multivariate elliptically contoured stable, and bivariate strictly stable distributions; 3- estimating the parameters of univariate symmetric stable, skew stable, Cauchy, multivariate elliptically contoured stable, and multivariate strictly stable distributions; 4- estimating the parameters of the mixture of symmetric stable and mixture of Cauchy distributions.

Maintained by Mahdi Teimouri. Last updated 6 years ago.

14.3 match 1 stars 1.18 score 15 scripts

r-forge

distr:Object Oriented Implementation of Distributions

S4-classes and methods for distributions.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

1.9 match 8.84 score 327 scripts 32 dependents

charvey23

AvInertia:Calculate the Inertial Properties of a Flying Bird

Tools to compute the center of gravity and moment of inertia tensor of any flying bird. The tools function by modeling a bird as a composite structure of simple geometric objects. This requires detailed morphological measurements of bird specimens although those obtained for the associated paper have been included in the package for use. Refer to the vignettes and supplementary material for detailed information on the package function.

Maintained by Christina Harvey. Last updated 3 years ago.

3.2 match 6 stars 5.00 score 33 scripts

christiangoueguel

ConfidenceEllipse:Computation of 2D and 3D Elliptical Joint Confidence Regions

Computing elliptical joint confidence regions at a specified confidence level. It provides the flexibility to estimate either classical or robust confidence regions, which can be visualized in 2D or 3D plots. The classical approach assumes normality and uses the mean and covariance matrix to define the confidence regions. Alternatively, the robustified version employs estimators like minimum covariance determinant (MCD) and M-estimator, making them less sensitive to outliers and departures from normality. Furthermore, the functions allow users to group the dataset based on categorical variables and estimate separate confidence regions for each group. This capability is particularly useful for exploring potential differences or similarities across subgroups within a dataset. Varmuza and Filzmoser (2009, ISBN:978-1-4200-5947-2). Johnson and Wichern (2007, ISBN:0-13-187715-1). Raymaekers and Rousseeuw (2019) <DOI:10.1080/00401706.2019.1677270>.

Maintained by Christian L. Goueguel. Last updated 11 months ago.

confidence-ellipse confidence-ellipsoid confidence-region multivariate-distribution outliers-detection robust-statistics

3.4 match 1 stars 4.70 score

calbertsen

otoclass:Otolith Classification and Proportion Estimation

Methods for classification and analysis of otoliths along with methods for estimating species proportions in samples.

Maintained by Christoffer Moesgaard Albertsen. Last updated 11 months ago.

contour-detection otolith-classification otolith-shape otoliths cpp

7.1 match 3 stars 2.18 score

cran

ellipticalsymmetry:Elliptical Symmetry Tests

Given the omnipresence of the assumption of elliptical symmetry, it is essential to be able to test whether that assumption actually holds true or not for the data at hand. This package provides several statistical tests for elliptical symmetry that are described in Babic et al. (2021) <arXiv:2011.12560v2>.

Maintained by Marko Palangetic. Last updated 4 years ago.

14.8 match 1.00 score

bioc

flowStats:Statistical methods for the analysis of flow cytometry data

Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package.

Maintained by Greg Finak. Last updated 5 months ago.

immunooncology flowcytometry cellbasedassays

1.8 match 13 stars 8.24 score 195 scripts 1 dependents

theropod1

gdi:Volumetric Analysis using Graphic Double Integration

Tools implementing an automated version of the graphic double integration technique (GDI) for volume implementation, and some other related utilities for paleontological image-analysis. GDI was first employed by Jerison (1973) <ISBN:9780323141086> and Hurlburt (1999) <doi:10.1080/02724634.1999.10011145> and is primarily used for volume or mass estimation of (extinct) animals. The package 'gdi' aims to make this technique as convenient and versatile as possible. The core functions of 'gdi' provide utilities for automatically measuring diameters from digital silhouettes provided as image files and calculating volume via graphic double integration with simple elliptical, superelliptical (following Motani 2001 <doi:10.1666/0094-8373(2001)027%3C0735:EBMFST%3E2.0.CO;2>) or complex cross-sectional models. Additionally, the package provides functions for estimating the center of mass position (COM), the moment of inertia (I) for 3D shapes and the second moment of area (Ix, Iy, Iz) of 2D cross-sections, as well as for visualization of results.

Maintained by Darius Nau. Last updated 11 months ago.

5.2 match 2.68 score 16 scripts

karlines

ReacTran:Reactive Transport Modelling in 1d, 2d and 3d

Routines for developing models that describe reaction and advective-diffusive transport in one, two or three dimensions. Includes transport routines in porous media, in estuaries, and in bodies with variable shape.

Maintained by Karline Soetaert. Last updated 8 years ago.

fortran

2.8 match 6 stars 4.57 score 52 scripts

wasquith

lmomco:L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions

Extensive functions for Lmoments (LMs) and probability-weighted moments (PWMs), distribution parameter estimation, LMs for distributions, LM ratio diagrams, multivariate Lcomoments, and asymmetric (asy) trimmed LMs (TLMs). Maximum likelihood and maximum product spacings estimation are available. Right-tail and left-tail LM censoring by threshold or indicator variable are available. LMs of residual (resid) and reversed (rev) residual life are implemented along with 13 quantile operators for reliability analyses. Exact analytical bootstrap estimates of order statistics, LMs, and LM var-covars are available. Harri-Coble Tau34-squared Normality Test is available. Distributions with L, TL, and added (+) support for right-tail censoring (RC) encompass: Asy Exponential (Exp) Power [L], Asy Triangular [L], Cauchy [TL], Eta-Mu [L], Exp. [L], Gamma [L], Generalized (Gen) Exp Poisson [L], Gen Extreme Value [L], Gen Lambda [L, TL], Gen Logistic [L], Gen Normal [L], Gen Pareto [L+RC, TL], Govindarajulu [L], Gumbel [L], Kappa [L], Kappa-Mu [L], Kumaraswamy [L], Laplace [L], Linear Mean Residual Quantile Function [L], Normal [L], 3p log-Normal [L], Pearson Type III [L], Polynomial Density-Quantile 3 and 4 [L], Rayleigh [L], Rev-Gumbel [L+RC], Rice [L], Singh Maddala [L], Slash [TL], 3p Student t [L], Truncated Exponential [L], Wakeby [L], and Weibull [L].

Maintained by William Asquith. Last updated 1 months ago.

flood-frequency-analysis l-moments mle-estimation mps-estimation probability-distribution rainfall-frequency-analysis reliability-analysis risk-analysis survival-analysis

1.6 match 2 stars 8.06 score 458 scripts 38 dependents

philboileau

cvCovEst:Cross-Validated Covariance Matrix Estimation

An efficient cross-validated approach for covariance matrix estimation, particularly useful in high-dimensional settings. This method relies upon the theory of high-dimensional loss-based covariance matrix estimator selection developed by Boileau et al. (2022) <doi:10.1080/10618600.2022.2110883> to identify the optimal estimator from among a prespecified set of candidates.

Maintained by Philippe Boileau. Last updated 1 years ago.

covariance-matrix-estimation cross-validation high-dimensional-statistics nonparametric-statistics

1.8 match 13 stars 6.78 score 26 scripts 2 dependents

jonasmoss

alphaci:Confidence Intervals for Coefficient Alpha and Standardized Alpha

Calculate confidence intervals for alpha and standardized alpha using asymptotic theory or the studentized bootstrap, with or without transformations. Supports the asymptotic distribution-free method of Maydeu-Olivares, et al. (2007) <doi:10.1037/1082-989X.12.2.157>, the pseudo-elliptical method of Yuan & Bentler (2002) <doi:10.1007/BF02294845>, and the normal method of van Zyl et al. (1999) <doi:10.1007/BF02296146>, for both coefficient alpha and standardized alpha.

Maintained by Jonas Moss. Last updated 1 years ago.

2.5 match 4.00 score 1 scripts

egarpor

rotasym:Tests for Rotational Symmetry on the Hypersphere

Implementation of the tests for rotational symmetry on the hypersphere proposed in García-Portugués, Paindaveine and Verdebout (2020) <doi:10.1080/01621459.2019.1665527>. The package also implements the proposed distributions on the hypersphere, based on the tangent-normal decomposition, and allows for the replication of the data application considered in the paper.

Maintained by Eduardo García-Portugués. Last updated 5 days ago.

circular-statistics directional-statistics goodness-of-fit semiparametric statistics cpp

2.0 match 2 stars 4.68 score 32 scripts 5 dependents

sanfordweisberg

dr:Methods for Dimension Reduction for Regression

Functions, methods, and datasets for fitting dimension reduction regression, using slicing (methods SAVE and SIR), Principal Hessian Directions (phd, using residuals and the response), and an iterative IRE. Partial methods, that condition on categorical predictors are also available. A variety of tests, and stepwise deletion of predictors, is also included. Also included is code for computing permutation tests of dimension. Adding additional methods of estimating dimension is straightforward. For documentation, see the vignette in the package. With version 3.0.4, the arguments for dr.step have been modified.

Maintained by Sanford Weisberg. Last updated 10 years ago.

1.9 match 4.87 score 122 scripts 10 dependents

chstock

DTComPair:Comparison of Binary Diagnostic Tests in a Paired Study Design

Comparison of the accuracy of two binary diagnostic tests in a "paired" study design, i.e. when each test is applied to each subject in the study.

Maintained by Christian Stock. Last updated 5 months ago.

clinical-epidemiology comparative-analysis diagnosis diagnostic-accuracy-studies diagnostic-likelihood-ratio diagnostic-tests medicine predictive-value sensitivity specificity

1.7 match 1 stars 5.07 score 47 scripts

swihart

mvpd:Multivariate Product Distributions for Elliptically Contoured Distributions

Estimates multivariate subgaussian stable densities and probabilities as well as generates random variates using product distribution theory. A function for estimating the parameters from data to fit a distribution to data is also provided, using the method from Nolan (2013) <doi:10.1007/s00180-013-0396-7>.

Maintained by Bruce Swihart. Last updated 1 years ago.

2.9 match 2.70 score 8 scripts

theussl

fMultivar:Rmetrics - Modeling of Multivariate Financial Return Distributions

A collection of functions inspired by Venables and Ripley (2002) <doi:10.1007/978-0-387-21706-2> and Azzalini and Capitanio (1999) <arXiv:0911.2093> to manage, investigate and analyze bivariate and multivariate data sets of financial returns.

Maintained by Stefan Theussl. Last updated 2 years ago.

2.0 match 3.69 score 99 scripts 7 dependents

bioc

tidySpatialExperiment:SpatialExperiment with tidy principles

tidySpatialExperiment provides a bridge between the SpatialExperiment package and the tidyverse ecosystem. It creates an invisible layer that allows you to interact with a SpatialExperiment object as if it were a tibble; enabling the use of functions from dplyr, tidyr, ggplot2 and plotly. But, underneath, your data remains a SpatialExperiment object.

Maintained by William Hutchison. Last updated 5 months ago.

infrastructure rnaseq geneexpression sequencing spatial transcriptomics singlecell

1.3 match 6 stars 5.88 score 12 scripts

rpbrowne

leptokurticMixture:Implements Parsimonious Finite Mixtures of Multivariate Elliptical Leptokurtic-Normals

A way to fit Parsimonious Finite Mixtures of Multivariate Elliptical Leptokurtic-Normals. Two methods of estimation are implemented.

Maintained by Ryan Browne. Last updated 2 years ago.

openblas

6.8 match 1.00 score

euctrl-pru

nvctr:The n-vector Approach to Geographical Position Calculations using an Ellipsoidal Model of Earth

The n-vector framework uses the normal vector to the Earth ellipsoid (called n-vector) as a non-singular position representation that turns out to be very convenient for practical position calculations. The n-vector is simple to use and gives exact answers for all global positions, and all distances, for both ellipsoidal and spherical Earth models. This package is a translation of the 'Matlab' library from FFI, the Norwegian Defence Research Establishment, as described in Gade (2010) <doi:10.1017/S0373463309990415>.

Maintained by Enrico Spinielli. Last updated 11 months ago.

geographical-positions n-vector

1.2 match 10 stars 5.19 score 31 scripts

wangyalin09

MKendall:Matrix Kendall's Tau and Matrix Elliptical Factor Model

Large-scale matrix-variate data have been widely observed nowadays in various research areas such as finance, signal processing and medical imaging. Modelling matrix-valued data by matrix-elliptical family not only provides a flexible way to handle heavy-tail property and tail dependencies, but also maintains the intrinsic row and column structure of random matrices. We proposed a new tool named matrix Kendall's tau which is efficient for analyzing random elliptical matrices. By applying this new type of Kendell’s tau to the matrix elliptical factor model, we propose a Matrix-type Robust Two-Step (MRTS) method to estimate the loading and factor spaces. See the details in He at al. (2022) <arXiv:2207.09633>. In this package, we provide the algorithms for calculating sample matrix Kendall's tau, the MRTS method and the Matrix Kendall's tau Eigenvalue-Ratio (MKER) method which is used for determining the number of factors.

Maintained by Yalin Wang. Last updated 1 years ago.

5.4 match 1.00 score

dariorlual

rPACI:Placido Analysis of Corneal Irregularity

Analysis of corneal data obtained from a Placido disk corneal topographer with calculation of irregularity indices. This package performs analyses of corneal data obtained from a Placido disk corneal topographer, with the calculation of the Placido irregularity indices and the posterior analysis. The package is intended to be easy to use by a practitioner, providing a simple interface and yielding easily interpretable results. A corneal topographer is an ophthalmic clinical device that obtains measurements in the cornea (the anterior part of the eye). A Placido disk corneal topographer makes use of the Placido disk [Rowsey et al. (1981)]<doi:10.1001/archopht.1981.03930011093022>, which produce a circular pattern of measurement nodes. The raw information measured by such a topographer is used by practitioners to analyze curvatures, to study optical aberrations, or to diagnose specific conditions of the eye (e.g. keratoconus, an important corneal disease). The rPACI package allows the calculation of the corneal irregularity indices described in [Castro-Luna et al. (2020)]<doi:10.1016%2Fj.clae.2019.12.006>, [Ramos-Lopez et al. (2013)]<doi:10.1097%2FOPX.0b013e3182843f2a>, and [Ramos-Lopez et al. (2011)]<doi:10.1097/opx.0b013e3182279ff8>. It provides a simple interface to read corneal topography data files as exported by a typical Placido disk topographer, to compute the irregularity indices mentioned before, and to display summary plots that are easy to interpret for a clinician.

Maintained by Darío Ramos-López. Last updated 3 years ago.

1.3 match 1 stars 4.30 score 9 scripts

cran

conicfit:Algorithms for Fitting Circles, Ellipses and Conics Based on the Work by Prof. Nikolai Chernov

Geometric circle fitting with Levenberg-Marquardt (a, b, R), Levenberg-Marquardt reduced (a, b), Landau, Spath and Chernov-Lesort. Algebraic circle fitting with Taubin, Kasa, Pratt and Fitzgibbon-Pilu-Fisher. Geometric ellipse fitting with ellipse LMG (geometric parameters) and conic LMA (algebraic parameters). Algebraic ellipse fitting with Fitzgibbon-Pilu-Fisher and Taubin.

Maintained by Jose Gama. Last updated 9 years ago.

3.0 match 1.78 score 2 dependents

windwill

cascsim:Casualty Actuarial Society Individual Claim Simulator

It is an open source insurance claim simulation engine sponsored by the Casualty Actuarial Society. It generates individual insurance claims including open claims, reopened claims, incurred but not reported claims and future claims. It also includes claim data fitting functions to help set simulation assumptions. It is useful for claim level reserving analysis. Parodi (2013) <https://www.actuaries.org.uk/documents/triangle-free-reserving-non-traditional-framework-estimating-reserves-and-reserve-uncertainty>.

Maintained by Kailan Shang. Last updated 5 years ago.

1.8 match 2.99 score 98 scripts

cran

otrimle:Robust Model-Based Clustering

Performs robust cluster analysis allowing for outliers and noise that cannot be fitted by any cluster. The data are modelled by a mixture of Gaussian distributions and a noise component, which is an improper uniform distribution covering the whole Euclidean space. Parameters are estimated by (pseudo) maximum likelihood. This is fitted by a EM-type algorithm. See Coretto and Hennig (2016) <doi:10.1080/01621459.2015.1100996>, and Coretto and Hennig (2017) <https://jmlr.org/papers/v18/16-382.html>.

Maintained by Pietro Coretto. Last updated 4 years ago.

3.5 match 1 stars 1.48 score 1 dependents

lafaye

ECGofTestDx:A Goodness-of-Fit Test for Elliptical Distributions with Diagnostic Capabilities

A goodness-of-fit test for elliptical distributions with diagnostic capabilities. Gilles R. Ducharme, Pierre Lafaye de Micheaux (2020) <doi:10.1016/j.jmva.2020.104602>.

Maintained by Pierre Lafaye De Micheaux. Last updated 5 months ago.

5.1 match 1.00 score 1 scripts

rucknium

rbch:Extraction and Analysis of Data from the Bitcoin Cash (BCH) Blockchain

Issues RPC-JSON calls to 'bitcoind', the daemon of Bitcoin Cash (BCH), to extract transaction data from the blockchain. BCH is a fork of Bitcoin that permits a greater number of transactions per second. A BCH daemon is available under an MIT license from the Bitcoin Unlimited website <https://www.bitcoinunlimited.info>.

Maintained by Rucknium. Last updated 4 months ago.

2.0 match 3 stars 2.48 score 7 scripts

davidbolin

rSPDE:Rational Approximations of Fractional Stochastic Partial Differential Equations

Functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main references for rSPDE are Bolin, Simas and Xiong (2023) <doi:10.1080/10618600.2023.2231051> for the covariance-based method and Bolin and Kirchner (2020) <doi:10.1080/10618600.2019.1665537> for the operator-based rational approximation. These can be generated by the citation function in R.

Maintained by David Bolin. Last updated 10 days ago.

0.5 match 11 stars 7.57 score 188 scripts 3 dependents

cran

mvst:Bayesian Inference for the Multivariate Skew-t Model

Estimates the multivariate skew-t and nested models, as described in the articles Liseo, B., Parisi, A. (2013). Bayesian inference for the multivariate skew-normal model: a population Monte Carlo approach. Comput. Statist. Data Anal. <doi:10.1016/j.csda.2013.02.007> and in Parisi, A., Liseo, B. (2017). Objective Bayesian analysis for the multivariate skew-t model. Statistical Methods & Applications <doi: 10.1007/s10260-017-0404-0>.

Maintained by Antonio Parisi. Last updated 1 years ago.

gsl

3.4 match 1.11 score 13 scripts

cran

astrodatR:Astronomical Data

A collection of 19 datasets from contemporary astronomical research. They are described the textbook `Modern Statistical Methods for Astronomy with R Applications' by Eric D. Feigelson and G. Jogesh Babu (Cambridge University Press, 2012, Appendix C) or on the website of Penn State's Center for Astrostatistics (http://astrostatistics.psu.edu/datasets). These datasets can be used to exercise methodology involving: density estimation; heteroscedastic measurement errors; contingency tables; two-sample hypothesis tests; spatial point processes; nonlinear regression; mixture models; censoring and truncation; multivariate analysis; classification and clustering; inhomogeneous Poisson processes; periodic and stochastic time series analysis.

Maintained by "Eric D., Feigelson". Last updated 11 years ago.

3.8 match 1 stars 1.00 score 8 scripts

jmmonnet

lidaRtRee:Forest Analysis with Airborne Laser Scanning (LiDAR) Data

Provides functions for forest objects detection, structure metrics computation, model calibration and mapping with airborne laser scanning: co-registration of field plots (Monnet and Mermin (2014) <doi:10.3390/f5092307>); tree detection (method 1 in Eysn et al. (2015) <doi:10.3390/f6051721>) and segmentation; forest parameters estimation with the area-based approach: model calibration with ground reference, and maps export (Aussenac et al. (2023) <doi:10.12688/openreseurope.15373.2>); extraction of both physical (gaps, edges, trees) and statistical features useful for e.g. habitat suitability modeling (Glad et al. (2020) <doi:10.1002/rse2.117>) and forest maturity mapping (Fuhr et al. (2022) <doi:10.1002/rse2.274>).

Maintained by Jean-Matthieu Monnet. Last updated 2 months ago.

1.7 match 3 stars 2.18 score

cran

Directional:A Collection of Functions for Directional Data Analysis

A collection of functions for directional data (including massive data, with millions of observations) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include: a) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2018). "An elliptically symmetric angular Gaussian distribution". Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). "Comparison of discriminant analysis methods on the sphere". Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. <doi:10.1007/s11222-019-09872-2>. d) Tsagris M. and Alenazi A. (2024). "An investigation of hypothesis testing procedures for circular and spherical mean vectors". Communications in Statistics-Simulation and Computation, 53(3): 1387--1408. <doi:10.1080/03610918.2022.2045499>. e) Yu Z. and Huang X. (2024). A new parameterization for elliptically symmetric angular Gaussian distributions of arbitrary dimension. Electronic Journal of Statistics, 18(1): 301--334. <doi:10.1214/23-EJS2210>. f) Tsagris M. and Alzeley O. (2024). "Circular and spherical projected Cauchy distributions: A Novel Framework for Circular and Directional Data Modeling". Australian & New Zealand Journal of Statistics (Accepted for publication). <doi:10.1111/anzs.12434>. g) Tsagris M., Papastamoulis P. and Kato S. (2024). "Directional data analysis: spherical Cauchy or Poisson kernel-based distribution". Statistics and Computing (Accepted for publication). <doi:10.48550/arXiv.2409.03292>.

Maintained by Michail Tsagris. Last updated 1 months ago.

0.8 match 3 stars 4.06 score 3 dependents

hughjonesd

ggmagnify:Create a Magnified Inset of Part of a "Ggplot" Object

Creates a magnified inset of a ggplot, with projection lines and borders around the target area and inset, plus optional shadow. Rectangular, elliptical or arbitrary regions can be magnified. Works with facets and maps. Geoms can optionally be recomputed within the inset area.

Maintained by David Hugh-Jones. Last updated 9 months ago.

ggplot graphics

0.5 match 277 stars 5.73 score 97 scripts

japhir

snvecR:Calculate Earth’s Obliquity and Precession in the Past

Easily calculate precession and obliquity from an orbital solution (defaults to ZB18a from Zeebe and Lourens (2019) <doi:10.1126/science.aax0612>) and assumed or reconstructed values for dynamical ellipticity (Ed) and tidal dissipation (Td). This is a translation and adaptation of the 'C'-code in the supplementary material to Zeebe and Lourens (2022) <doi:10.1029/2021PA004349>, with further details on the methodology described in Zeebe (2022) <doi:10.3847/1538-3881/ac80f8>. The name of the 'C'-routine is 'snvec', which refers to the key units of computation: spin vector s and orbit normal vector n.

Maintained by Ilja Kocken. Last updated 7 days ago.

0.5 match 4 stars 5.51 score 4 scripts

chedgala

MomTrunc:Moments of Folded and Doubly Truncated Multivariate Distributions

It computes arbitrary products moments (mean vector and variance-covariance matrix), for some double truncated (and folded) multivariate distributions. These distributions belong to the family of selection elliptical distributions, which includes well known skewed distributions as the unified skew-t distribution (SUT) and its particular cases as the extended skew-t (EST), skew-t (ST) and the symmetric student-t (T) distribution. Analogous normal cases unified skew-normal (SUN), extended skew-normal (ESN), skew-normal (SN), and symmetric normal (N) are also included. Density, probabilities and random deviates are also offered for these members.

Maintained by Christian E. Galarza. Last updated 5 months ago.

generation-algorithms moments probability-statistics openblas cpp

0.5 match 4.81 score 17 scripts 7 dependents

bpfaff

rbtc:Bitcoin API

Implementation of the RPC-JSON API for Bitcoin and utility functions for address creation and content analysis of the blockchain.

Maintained by Bernhard Pfaff. Last updated 5 months ago.

2.0 match 1.15 score 14 scripts

jpnolan

gensphere:Generalized Spherical Distributions

Define and compute with generalized spherical distributions - multivariate probability laws that are specified by a star shaped contour (directional behavior) and a radial component. The methods are described in Nolan (2016) <doi:10.1186/s40488-016-0053-0>.

Maintained by John P Nolan. Last updated 4 years ago.

2.3 match 1.00 score 2 scripts

cran

sym.arma:Autoregressive and Moving Average Symmetric Models

Functions for fitting the Autoregressive and Moving Average Symmetric Model for univariate time series introduced by Maior and Cysneiros (2018), <doi:10.1007/s00362-016-0753-z>. Fitting method: conditional maximum likelihood estimation. For details see: Wei (2006), Time Series Analysis: Univariate and Multivariate Methods, Section 7.2.

Maintained by Vinicius Quintas Souto Maior. Last updated 6 years ago.

2.3 match 1.00 score

rosarialo

CAvariants:Correspondence Analysis Variants

Provides six variants of two-way correspondence analysis (ca): simple ca, singly ordered ca, doubly ordered ca, non symmetrical ca, singly ordered non symmetrical ca, and doubly ordered non symmetrical ca.

Maintained by Rosaria Lombardo. Last updated 1 years ago.

1.7 match 1.18 score 15 scripts

drjohanlk

kollaR:Filtering, Visualization and Analysis of Eye Tracking Data

Functions for analysing eye tracking data, including event detection (I-VT, I-DT and two means clustering), visualizations and area of interest (AOI) based analyses. See separate documentation for each function. The principles underlying I-VT and I-DT filters are described in Salvucci & Goldberg (2000,\doi{10.1145/355017.355028}). Two-means clustering is described in Hessels et al. (2017, \doi{10.3758/s13428-016-0822-1}).

Maintained by Johan Lundin Kleberg. Last updated 25 days ago.

1.5 match 1.30 score

jwood000

RcppBigIntAlgos:Factor Big Integers with the Parallel Quadratic Sieve

Features the multiple polynomial quadratic sieve (MPQS) algorithm for factoring large integers and a vectorized factoring function that returns the complete factorization of an integer. The MPQS is based off of the seminal work of Carl Pomerance (1984) <doi:10.1007/3-540-39757-4_17> along with the modification of multiple polynomials introduced by Peter Montgomery and J. Davis as outlined by Robert D. Silverman (1987) <doi:10.1090/S0025-5718-1987-0866119-8>. Utilizes the C library GMP (GNU Multiple Precision Arithmetic). For smaller integers, a simple Elliptic Curve algorithm is attempted followed by a constrained version of Pollard's rho algorithm. The Pollard's rho algorithm is the same algorithm used by the factorize function in the 'gmp' package.

Maintained by Joseph Wood. Last updated 10 months ago.

algorithm gmp integer-factorization mpqs prime-factorizations primes quadratic-sieve quadratic-sieve-algorithm cpp

0.5 match 13 stars 3.81 score 8 scripts

anniesbooth

deepgp:Bayesian Deep Gaussian Processes using MCMC

Performs Bayesian posterior inference for deep Gaussian processes following Sauer, Gramacy, and Higdon (2023, <doi:10.48550/arXiv.2012.08015>). See Sauer (2023, <http://hdl.handle.net/10919/114845>) for comprehensive methodological details and <https://bitbucket.org/gramacylab/deepgp-ex/> for a variety of coding examples. Models are trained through MCMC including elliptical slice sampling of latent Gaussian layers and Metropolis-Hastings sampling of kernel hyperparameters. Vecchia-approximation for faster computation is implemented following Sauer, Cooper, and Gramacy (2023, <doi:10.48550/arXiv.2204.02904>). Optional monotonic warpings are implemented following Barnett et al. (2024, <doi:10.48550/arXiv.2408.01540>). Downstream tasks include sequential design through active learning Cohn/integrated mean squared error (ALC/IMSE; Sauer, Gramacy, and Higdon, 2023), optimization through expected improvement (EI; Gramacy, Sauer, and Wycoff, 2022 <doi:10.48550/arXiv.2112.07457>), and contour location through entropy (Booth, Renganathan, and Gramacy, 2024 <doi:10.48550/arXiv.2308.04420>). Models extend up to three layers deep; a one layer model is equivalent to typical Gaussian process regression. Incorporates OpenMP and SNOW parallelization and utilizes C/C++ under the hood.

Maintained by Annie S. Booth. Last updated 7 months ago.

openblas cpp openmp

0.5 match 2 stars 3.45 score 14 scripts

cran

HDRFA:High-Dimensional Robust Factor Analysis

Factor models have been widely applied in areas such as economics and finance, and the well-known heavy-tailedness of macroeconomic/financial data should be taken into account when conducting factor analysis. We propose two algorithms to do robust factor analysis by considering the Huber loss. One is based on minimizing the Huber loss of the idiosyncratic error's L2 norm, which turns out to do Principal Component Analysis (PCA) on the weighted sample covariance matrix and thereby named as Huber PCA. The other one is based on minimizing the element-wise Huber loss, which can be solved by an iterative Huber regression algorithm. In this package we also provide the code for traditional PCA, the Robust Two Step (RTS) method by He et al. (2022) and the Quantile Factor Analysis (QFA) method by Chen et al. (2021) and He et al. (2023).

Maintained by Dong Liu. Last updated 8 months ago.

1.7 match 1.00 score 1 scripts

spencerm89

hysteresis:Tools for Modeling Rate-Dependent Hysteretic Processes and Ellipses

Fit, summarize and plot sinusoidal hysteretic processes using: two-step simple harmonic least squares, ellipse-specific non-linear least squares, the direct method, geometric least squares or linear least squares. See Yang, F and A. Parkhurst, "Efficient Estimation of Elliptical Hysteresis with Application to the Characterization of Heat Stress" <DOI:10.1007/s13253-015-0213-6>.

Maintained by Spencer Maynes. Last updated 1 years ago.

0.5 match 1 stars 2.98 score 19 scripts

kazwd2008

RMSD:Refined Modified Stahel-Donoho Estimators for Outlier Detection

A function for multivariate outlier detection named Modified Stahel-Donoho (MSD) estimators is contained. The function is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. The function is called the single core version in Wada & Tsubaki (2013) <doi:10.1109/CLOUDCOM-ASIA.2013.86> and evaluated with other methods in Wada, Kawano & Tsubaki (2020) <doi:10.17713/ajs.v49i2.872>.

Maintained by Kazumi Wada. Last updated 1 years ago.

0.5 match 2.70 score 1 scripts

kazwd2008

RMSDp:Refined Modified Stahel-Donoho (MSD) Estimators for Outlier Detection (Parallel Version)

A parallel function for multivariate outlier detection named modified Stahel-Donoho estimators is contained in this package. The function RMSDp() is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. This function is for higher dimensional datasets that cannot be handled by a single core function RMSD() included in 'RMSD' package. See Wada and Tsubaki (2013) <doi:10.1109/CLOUDCOM-ASIA.2013.86> for the detail of the algorithm.

Maintained by Kazumi Wada. Last updated 9 months ago.

0.5 match 2.70 score

cran

SyScSelection:Systematic Scenario Selection for Stress Testing

Quasi-Monte-Carlo algorithm for systematic generation of shock scenarios from an arbitrary multivariate elliptical distribution. The algorithm selects a systematic mesh of arbitrary fineness that approximately evenly covers an isoprobability ellipsoid in d dimensions (Flood, Mark D. & Korenko, George G. (2013) <doi:10.1080/14697688.2014.926018>). This package is the 'R' analogy to the 'Matlab' code published by Flood & Korenko in above-mentioned paper.

Maintained by Merlin Kopfmann. Last updated 4 years ago.

0.5 match 2.70 score 3 scripts

roy-sr-007

bayesestdft:Estimating the Degrees of Freedom of the Student's t-Distribution under a Bayesian Framework

A Bayesian framework to estimate the Student's t-distribution's degrees of freedom is developed. Markov Chain Monte Carlo sampling routines are developed as in <doi:10.3390/axioms11090462> to sample from the posterior distribution of the degrees of freedom. A random walk Metropolis algorithm is used for sampling when Jeffrey's and Gamma priors are endowed upon the degrees of freedom. In addition, the Metropolis-adjusted Langevin algorithm for sampling is used under the Jeffrey's prior specification. The Log-normal prior over the degrees of freedom is posed as a viable choice with comparable performance in simulations and real-data application, against other prior choices, where an Elliptical Slice Sampler is used to sample from the concerned posterior.

Maintained by Somjit Roy. Last updated 2 months ago.

0.5 match 1 stars 2.70 score 1 scripts

ggopalan

FastGP:Efficiently Using Gaussian Processes with Rcpp and RcppEigen

Contains Rcpp and RcppEigen implementations of matrix operations useful for Gaussian process models, such as the inversion of a symmetric Toeplitz matrix, sampling from multivariate normal distributions, evaluation of the log-density of a multivariate normal vector, and Bayesian inference for latent variable Gaussian process models with elliptical slice sampling (Murray, Adams, and MacKay 2010).

Maintained by Giri Gopalan. Last updated 9 years ago.

cpp

0.5 match 2.56 score 24 scripts 5 dependents

cran

cabootcrs:Bootstrap Confidence Regions for Simple and Multiple Correspondence Analysis

Performs simple correspondence analysis on a two-way contingency table, or multiple correspondence analysis (homogeneity analysis) on data with p categorical variables, and produces bootstrap-based elliptical confidence regions around the projected coordinates for the category points. Includes routines to plot the results in a variety of styles. Also reports the standard numerical output for correspondence analysis.

Maintained by Trevor Ringrose. Last updated 3 years ago.

0.5 match 1.70 score

cran

FPDclustering:PD-Clustering and Related Methods

Probabilistic distance clustering (PD-clustering) is an iterative, distribution-free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership under the constraint that the product of the probability and the distance of each point to any cluster center is a constant. PD-clustering is a flexible method that can be used with elliptical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different sizes. GPDC and TPDC use a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high-dimensional data sets.

Maintained by Cristina Tortora. Last updated 11 days ago.

0.5 match 1.60 score

cran

mixSPE:Mixtures of Power Exponential and Skew Power Exponential Distributions for Use in Model-Based Clustering and Classification

Mixtures of skewed and elliptical distributions are implemented using mixtures of multivariate skew power exponential and power exponential distributions, respectively. A generalized expectation-maximization framework is used for parameter estimation. See citation() for how to cite.

Maintained by Utkarsh J. Dang. Last updated 1 years ago.

0.5 match 1.00 score

cran

csn:Closed Skew-Normal Distribution

Provides functions for computing the density and the log-likelihood function of closed-skew normal variates, and for generating random vectors sampled from this distribution. See Gonzalez-Farias, G., Dominguez-Molina, J., and Gupta, A. (2004). The closed skew normal distribution, Skew-elliptical distributions and their applications: a journey beyond normality, Chapman and Hall/CRC, Boca Raton, FL, pp. 25-42.

Maintained by Dmitry Pavlyuk. Last updated 10 years ago.

0.5 match 1.00 score

ptaler

LeArEst:Border and Area Estimation of Data Measured with Additive Error

Provides methods for estimating borders of uniform distribution on the interval (one-dimensional) and on the elliptical domain (two-dimensional) under measurement errors. For one-dimensional case, it also estimates the length of underlying uniform domain and tests the hypothesized length against two-sided or one-sided alternatives. For two-dimensional case, it estimates the area of underlying uniform domain. It works with numerical inputs as well as with pictures in JPG format.

Maintained by Petar Taler. Last updated 6 years ago.

0.5 match 1.00 score

cran

MSclust:Multiple-Scaled Clustering

Model based clustering using the multivariate multiple Scaled t (MST) and multivariate multiple scaled contaminated normal (MSCN) distributions. The MST is an extension of the multivariate Student-t distribution to include flexible tail behaviors, Forbes, F. & Wraith, D. (2014) <doi:10.1007/s11222-013-9414-4>. The MSCN represents a heavy-tailed generalization of the multivariate normal (MN) distribution to model elliptical contoured scatters in the presence of mild outliers (also referred to as "bad" points) and automatically detect bad points, Punzo, A. & Tortora, C. (2021) <doi:10.1177/1471082X19890935>.

Maintained by Cristina Tortora. Last updated 11 months ago.

0.5 match 1.00 score