Showing 21 of total 21 results (show query)
bwrc
edf:Read Data from European Data Format (EDF and EDF+) Files
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.
Maintained by Andreas Henelius. Last updated 9 years ago.
68.8 match 19 stars 4.02 score 11 scripts
alexander-pastukhov
eyelinkReader:Import Gaze Data for EyeLink Eye Tracker
Import gaze data from edf files generated by the SR Research <https://www.sr-research.com/> EyeLink eye tracker. Gaze data, both recorded events and samples, is imported per trial. The package allows to extract events of interest, such as saccades, blinks, etc. as well as recorded variables and custom events (areas of interest, triggers) into separate tables. The package requires EDF API library that can be obtained at <https://www.sr-research.com/support/>.
Maintained by Alexander Pastukhov. Last updated 3 months ago.
edfeye-trackingeyelinksr-researchcpp
18.9 match 13 stars 6.52 score 34 scripts
dankelley
oce:Analysis of Oceanographic Data
Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature. This package is discussed extensively by Kelley (2018) "Oceanographic Analysis with R" <doi:10.1007/978-1-4939-8844-0>.
Maintained by Dan Kelley. Last updated 1 days ago.
5.4 match 146 stars 15.42 score 4.2k scripts 18 dependents
dipterix
ieegio:File IO for Intracranial Electroencephalography
Integrated toolbox supporting common file formats used for intracranial Electroencephalography (iEEG) and deep-brain stimulation (DBS) study.
Maintained by Zhengjia Wang. Last updated 3 days ago.
bci2000brainbrainvisiondbsedfelectrophysiologyephysfreesurferieegneuroimagingneuroscienceniftinwb-format
12.8 match 5.65 score 10 scripts 1 dependents
gavinsimpson
gratia:Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'
Graceful 'ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well as 'tidyverse' compatible representations of estimated smooths.
Maintained by Gavin L. Simpson. Last updated 10 hours ago.
distributional-regressiongamgammgeneralized-additive-mixed-modelsgeneralized-additive-modelsggplot2glmlmmgcvpenalized-splinerandom-effectssmoothingsplines
3.3 match 217 stars 12.99 score 1.6k scripts 2 dependents
gamlss-dev
gamlss:Generalized Additive Models for Location Scale and Shape
Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.
Maintained by Mikis Stasinopoulos. Last updated 4 months ago.
3.3 match 16 stars 11.23 score 2.0k scripts 49 dependents
cran
edfReader:Reading EDF(+) and BDF(+) Files
Reads European Data Format files EDF and EDF+, see <http://www.edfplus.info>, BioSemi Data Format files BDF, see <http://www.biosemi.com/faq/file_format.htm>, and BDF+ files, see <http://www.teuniz.net/edfbrowser/bdfplus%20format%20description.html>. The files are read in two steps: first the header is read and then the signals (using the header object as a parameter).
Maintained by Jan Vis. Last updated 6 years ago.
13.0 match 2.71 score 17 scripts 1 dependentscran
circular:Circular Statistics
Circular Statistics, from "Topics in circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.
Maintained by Eduardo García-Portugués. Last updated 7 months ago.
4.5 match 7 stars 7.76 score 1.1k scripts 40 dependentscran
mgcv:Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Maintained by Simon Wood. Last updated 1 years ago.
2.3 match 32 stars 12.71 score 17k scripts 7.8k dependents
rich-iannone
DiagrammeR:Graph/Network Visualization
Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.
Maintained by Richard Iannone. Last updated 2 months ago.
graphgraph-functionsnetwork-graphproperty-graphvisualization
1.8 match 1.7k stars 15.18 score 3.8k scripts 87 dependents
harrysouthworth
texmex:Statistical Modelling of Extreme Values
Statistical extreme value modelling of threshold excesses, maxima and multivariate extremes. Univariate models for threshold excesses and maxima are the Generalised Pareto, and Generalised Extreme Value model respectively. These models may be fitted by using maximum (optionally penalised-)likelihood, or Bayesian estimation, and both classes of models may be fitted with covariates in any/all model parameters. Model diagnostics support the fitting process. Graphical output for visualising fitted models and return level estimates is provided. For serially dependent sequences, the intervals declustering algorithm of Ferro and Segers (2003) <doi:10.1111/1467-9868.00401> is provided, with diagnostic support to aid selection of threshold and declustering horizon. Multivariate modelling is performed via the conditional approach of Heffernan and Tawn (2004) <doi:10.1111/j.1467-9868.2004.02050.x>, with graphical tools for threshold selection and to diagnose estimation convergence.
Maintained by Harry Southworth. Last updated 1 years ago.
3.3 match 7 stars 6.92 score 66 scripts 1 dependents
ajmcneil
tscopula:Time Series Copula Models
Functions for the analysis of time series using copula models. The package is based on methodology described in the following references. McNeil, A.J. (2021) <doi:10.3390/risks9010014>, Bladt, M., & McNeil, A.J. (2021) <doi:10.1016/j.ecosta.2021.07.004>, Bladt, M., & McNeil, A.J. (2022) <doi:10.1515/demo-2022-0105>.
Maintained by Alexander McNeil. Last updated 24 days ago.
3.3 match 2 stars 5.53 score 12 scripts
bpfaff
QRM:Provides R-Language Code to Examine Quantitative Risk Management Concepts
Provides functions/methods to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Ruediger Frey, and Paul Embrechts.
Maintained by Bernhard Pfaff. Last updated 5 years ago.
3.3 match 4.53 score 181 scripts 5 dependents
alishinski
lavaanPlot:Path Diagrams for 'Lavaan' Models via 'DiagrammeR'
Plots path diagrams from models in 'lavaan' using the plotting functionality from the 'DiagrammeR' package. 'DiagrammeR' provides nice path diagrams via 'Graphviz', and these functions make it easy to generate these diagrams from a 'lavaan' path model without having to write the DOT language graph specification.
Maintained by Alex Lishinski. Last updated 1 years ago.
1.7 match 40 stars 8.33 score 294 scripts
chjackson
msmbayes:Bayesian Multi-State Models for Intermittently-Observed Data
Bayesian multi-state models for intermittently-observed data. Markov and phase-type semi-Markov models, and misclassification hidden Markov models.
Maintained by Christopher Jackson. Last updated 4 months ago.
3.3 match 4 stars 4.26 score 3 scripts
tvatter
gamCopula:Generalized Additive Models for Bivariate Conditional Dependence Structures and Vine Copulas
Implementation of various inference and simulation tools to apply generalized additive models to bivariate dependence structures and non-simplified vine copulas.
Maintained by Thibault Vatter. Last updated 5 years ago.
3.3 match 9 stars 3.77 score 13 scripts
r-forge
RHRV:Heart Rate Variability Analysis of ECG Data
Allows users to import data files containing heartbeat positions in the most broadly used formats, to remove outliers or points with unacceptable physiological values present in the time series, to plot HRV data, and to perform time domain, frequency domain and nonlinear HRV analysis. See Garcia et al. (2017) <DOI:10.1007/978-3-319-65355-6>.
Maintained by Leandro Rodriguez-Linares. Last updated 6 months ago.
1.8 match 6.79 score 63 scripts 1 dependents
giampmarra
GJRM:Generalised Joint Regression Modelling
Routines for fitting various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations' errors association, endogeneity, non-random sample selection or partial observability.
Maintained by Giampiero Marra. Last updated 5 months ago.
2.3 match 4 stars 4.10 score 67 scripts 5 dependentsr-forge
tramME:Transformation Models with Mixed Effects
Likelihood-based estimation of mixed-effects transformation models using the Template Model Builder ('TMB', Kristensen et al., 2016) <doi:10.18637/jss.v070.i05>. The technical details of transformation models are given in Hothorn et al. (2018) <doi:10.1111/sjos.12291>. Likelihood contributions of exact, randomly censored (left, right, interval) and truncated observations are supported. The random effects are assumed to be normally distributed on the scale of the transformation function, the marginal likelihood is evaluated using the Laplace approximation, and the gradients are calculated with automatic differentiation (Tamasi & Hothorn, 2021) <doi:10.32614/RJ-2021-075>. Penalized smooth shift terms can be defined using 'mgcv'.
Maintained by Balint Tamasi. Last updated 4 days ago.
1.9 match 4.12 score 1 scripts
a-hurst
eyelinker:Import ASC Files from EyeLink Eye Trackers
Imports plain-text ASC data files from EyeLink eye trackers into (relatively) tidy data frames for analysis and visualization.
Maintained by Austin Hurst. Last updated 4 years ago.
1.3 match 7 stars 5.45 score 20 scriptscran
asymmetry.measures:Asymmetry Measures for Probability Density Functions
Provides functions and examples for the weak and strong density asymmetry measures in the articles: "A measure of asymmetry", Patil, Patil and Bagkavos (2012) <doi:10.1007/s00362-011-0401-6> and "A measure of asymmetry based on a new necessary and sufficient condition for symmetry", Patil, Bagkavos and Wood (2014) <doi:10.1007/s13171-013-0034-z>. The measures provided here are useful for quantifying the asymmetry of the shape of a density of a random variable. The package facilitates implementation of the measures which are applicable in a variety of fields including e.g. probability theory, statistics and economics.
Maintained by Dimitrios Bagkavos. Last updated 5 years ago.
3.3 match 1.00 score