Showing 171 of total 171 results (show query)
hrbrmstr
ggalt:Extra Coordinate Systems, 'Geoms', Statistical Transformations, Scales and Fonts for 'ggplot2'
A compendium of new geometries, coordinate systems, statistical transformations, scales and fonts for 'ggplot2', including splines, 1d and 2d densities, univariate average shifted histograms, a new map coordinate system based on the 'PROJ.4'-library along with geom_cartogram() that mimics the original functionality of geom_map(), formatters for "bytes", a stat_stepribbon() function, increased 'plotly' compatibility and the 'StateFace' open source font 'ProPublica'. Further new functionality includes lollipop charts, dumbbell charts, the ability to encircle points and coordinate-system-based text annotations.
Maintained by Bob Rudis. Last updated 2 years ago.
geomggplot-extensionggplot2ggplot2-geomggplot2-scales
676 stars 12.60 score 2.3k scripts 7 dependents
jamesramsay5
fda:Functional Data Analysis
These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from <https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.
Maintained by James Ramsay. Last updated 4 months ago.
3 stars 11.88 score 2.0k scripts 142 dependents
robjhyndman
hdrcde:Highest Density Regions and Conditional Density Estimation
Computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate,and multimodal regression.
Maintained by Rob Hyndman. Last updated 2 years ago.
24 stars 10.38 score 128 scripts 158 dependents
refunders
refund:Regression with Functional Data
Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.
Maintained by Julia Wrobel. Last updated 6 months ago.
43 stars 10.11 score 472 scripts 17 dependents
moviedo5
fda.usc:Functional Data Analysis and Utilities for Statistical Computing
Routines for exploratory and descriptive analysis of functional data such as depth measurements, atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis of variance.
Maintained by Manuel Oviedo de la Fuente. Last updated 5 months ago.
functional-data-analysisfortran
12 stars 9.72 score 560 scripts 22 dependents
bioc
ggmsa:Plot Multiple Sequence Alignment using 'ggplot2'
A visual exploration tool for multiple sequence alignment and associated data. Supports MSA of DNA, RNA, and protein sequences using 'ggplot2'. Multiple sequence alignment can easily be combined with other 'ggplot2' plots, such as phylogenetic tree Visualized by 'ggtree', boxplot, genome map and so on. More features: visualization of sequence logos, sequence bundles, RNA secondary structures and detection of sequence recombinations.
Maintained by Guangchuang Yu. Last updated 3 months ago.
softwarevisualizationalignmentannotationmultiplesequencealignment
210 stars 9.35 score 196 scripts 2 dependents
andrewljackson
SIBER:Stable Isotope Bayesian Ellipses in R
Fits bi-variate ellipses to stable isotope data using Bayesian inference with the aim being to describe and compare their isotopic niche.
Maintained by Andrew Jackson. Last updated 10 months ago.
community-ecologyecologyniche-modellingstable-isotopesjagscpp
37 stars 9.15 score 187 scripts 1 dependentsbioc
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.
immunooncologyflowcytometrycellbasedassays
14 stars 8.27 score 195 scripts 1 dependentsrobjhyndman
demography:Forecasting Mortality, Fertility, Migration and Population Data
Functions for demographic analysis including lifetable calculations; Lee-Carter modelling; functional data analysis of mortality rates, fertility rates, net migration numbers; and stochastic population forecasting.
Maintained by Rob Hyndman. Last updated 4 months ago.
actuarialdemographyforecasting
74 stars 8.21 score 241 scripts 6 dependents
sbgraves237
Ecfun:Functions for 'Ecdat'
Functions and vignettes to update data sets in 'Ecdat' and to create, manipulate, plot, and analyze those and similar data sets.
Maintained by Spencer Graves. Last updated 4 months ago.
8.02 score 85 scripts 4 dependents
valeriapolicastro
robin:ROBustness in Network
Assesses the robustness of the community structure of a network found by one or more community detection algorithm to give indications about their reliability. It detects if the community structure found by a set of algorithms is statistically significant and compares the different selected detection algorithms on the same network. robin helps to choose among different community detection algorithms the one that better fits the network of interest. Reference in Policastro V., Righelli D., Carissimo A., Cutillo L., De Feis I. (2021) <https://journal.r-project.org/archive/2021/RJ-2021-040/index.html>.
Maintained by Valeria Policastro. Last updated 8 days ago.
19 stars 7.72 score 8 scripts
samhforbes
PupillometryR:A Unified Pipeline for Pupillometry Data
Provides a unified pipeline to clean, prepare, plot, and run basic analyses on pupillometry experiments.
Maintained by Samuel Forbes. Last updated 2 years ago.
44 stars 7.58 score 288 scripts 1 dependents
dboslab
expowo:An R package for mining global plant diversity and distribution data
Produces diversity estimates and species lists with associated global distribution for any vascular plant family and genus from 'Plants of the World Online' database <https://powo.science.kew.org/>, by interacting with the source code of each plant taxon page. It also creates global maps of species richness, graphics of species discoveries and nomenclatural changes over time. For more details
Maintained by Debora Zuanny. Last updated 5 days ago.
8 stars 7.44 score 64 scripts
alaninglis
vivid:Variable Importance and Variable Interaction Displays
A suite of plots for displaying variable importance and two-way variable interaction jointly. Can also display partial dependence plots laid out in a pairs plot or 'zenplots' style.
Maintained by Alan Inglis. Last updated 8 months ago.
21 stars 7.39 score 39 scripts
siacus
sde:Simulation and Inference for Stochastic Differential Equations
Companion package to the book Simulation and Inference for Stochastic Differential Equations With R Examples, ISBN 978-0-387-75838-1, Springer, NY. *
Maintained by Stefano Maria Iacus. Last updated 2 years ago.
7.08 score 178 scripts 15 dependents
unina-sfere
funcharts:Functional Control Charts
Provides functional control charts for statistical process monitoring of functional data, using the methods of Capezza et al. (2020) <doi:10.1002/asmb.2507>, Centofanti et al. (2021) <doi:10.1080/00401706.2020.1753581>, Capezza et al. (2024) <doi:10.1080/00401706.2024.2327346>, Capezza et al. (2024) <doi:10.1080/00224065.2024.2383674>, Centofanti et al. (2022) <doi:10.48550/arXiv.2205.06256>. The package is thoroughly illustrated in the paper of Capezza et al (2023) <doi:10.1080/00224065.2023.2219012>.
Maintained by Christian Capezza. Last updated 12 days ago.
2 stars 6.73 score 168 scripts
gloewing
fastFMM:Fast Functional Mixed Models using Fast Univariate Inference
Implementation of the fast univariate inference approach (Cui et al. (2022) <doi:10.1080/10618600.2021.1950006>, Loewinger et al. (2024) <doi:10.7554/eLife.95802.2>) for fitting functional mixed models. User guides and Python package information can be found at <https://github.com/gloewing/photometry_FLMM>.
Maintained by Erjia Cui. Last updated 5 days ago.
9 stars 6.51 score 22 scripts
benjaminhlina
nichetools:Complementary Package to 'nicheROVER' and 'SIBER'
Provides functions complementary to packages 'nicheROVER' and 'SIBER' allowing the user to extract Bayesian estimates from data objects created by the packages 'nicheROVER' and 'SIBER'. Please see the following publications for detailed methods on 'nicheROVER' and 'SIBER' Hansen et al. (2015) <doi:10.1890/14-0235.1>, Jackson et al. (2011) <do i:10.1111/j.1365-2656.2011.01806.x>, and Layman et al. (2007) <doi:10.1890/0012-9658(2007)88[42:CSIRPF]2.0.CO;2>, respectfully.
Maintained by Benjamin L. Hlina. Last updated 9 days ago.
2 stars 6.39 score 17 scripts
trackerproject
trackeR:Infrastructure for Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices
Provides infrastructure for handling running, cycling and swimming data from GPS-enabled tracking devices within R. The package provides methods to extract, clean and organise workout and competition data into session-based and unit-aware data objects of class 'trackeRdata' (S3 class). The information can then be visualised, summarised, and analysed through flexible and extensible methods. Frick and Kosmidis (2017) <doi: 10.18637/jss.v082.i07>, which is updated and maintained as one of the vignettes, provides detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality.
Maintained by Ioannis Kosmidis. Last updated 1 years ago.
90 stars 6.37 score 58 scripts 1 dependents
angelacar
TwoTimeScales:Analysis of Event Data with Two Time Scales
Analyse time to event data with two time scales by estimating a smooth hazard that varies over two time scales. If covariates are available, estimate a proportional hazards model with such a two-dimensional baseline hazard. Functions are provided to prepare the raw data for estimation, to estimate and to plot the two-dimensional smooth hazard. Extension to a competing risks model are implemented. For details about the method please refer to Carollo et al. (2024) <doi:10.1002/sim.10297>.
Maintained by Angela Carollo. Last updated 2 months ago.
9 stars 6.26 score 5 scripts
zhenkewu
baker:"Nested Partially Latent Class Models"
Provides functions to specify, fit and visualize nested partially-latent class models ( Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>; Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>; Wu and Chen (2021) <doi:10.1002/sim.8804>) for inference of population disease etiology and individual diagnosis. In the motivating Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities of interest sum to one hundred percent, the PERCH scientists frequently refer to them as population etiology pie and individual etiology pie, hence the name of the package.
Maintained by Zhenke Wu. Last updated 11 months ago.
bayesiancase-controllatent-class-analysisjagscpp
8 stars 6.00 score 21 scripts
bioc
UMI4Cats:UMI4Cats: Processing, analysis and visualization of UMI-4C chromatin contact data
UMI-4C is a technique that allows characterization of 3D chromatin interactions with a bait of interest, taking advantage of a sonication step to produce unique molecular identifiers (UMIs) that help remove duplication bias, thus allowing a better differential comparsion of chromatin interactions between conditions. This package allows processing of UMI-4C data, starting from FastQ files provided by the sequencing facility. It provides two statistical methods for detecting differential contacts and includes a visualization function to plot integrated information from a UMI-4C assay.
Maintained by Mireia Ramos-Rodriguez. Last updated 5 months ago.
qualitycontrolpreprocessingalignmentnormalizationvisualizationsequencingcoveragechromatinchromatin-interactiongenomicsumi4c
5 stars 5.57 score 7 scriptsbioc
spatialFDA:A Tool for Spatial Multi-sample Comparisons
spatialFDA is a package to calculate spatial statistics metrics. The package takes a SpatialExperiment object and calculates spatial statistics metrics using the package spatstat. Then it compares the resulting functions across samples/conditions using functional additive models as implemented in the package refund. Furthermore, it provides exploratory visualisations using functional principal component analysis, as well implemented in refund.
Maintained by Martin Emons. Last updated 1 months ago.
softwarespatialtranscriptomics
3 stars 5.18 score 6 scripts
julia-wrobel
mxfda:A Functional Data Analysis Package for Spatial Single Cell Data
Methods and tools for deriving spatial summary functions from single-cell imaging data and performing functional data analyses. Functions can be applied to other single-cell technologies such as spatial transcriptomics. Functional regression and functional principal component analysis methods are in the 'refund' package <https://cran.r-project.org/package=refund> while calculation of the spatial summary functions are from the 'spatstat' package <https://spatstat.org/>.
Maintained by Alex Soupir. Last updated 1 months ago.
1 stars 5.08 score 8 scriptsrefunders
refund.shiny:Interactive Plotting for Functional Data Analyses
Produces Shiny applications for different types of popular functional data analyses. The functional data analyses are implemented in the refund package, then refund.shiny reads in the refund object and implements an object-specific set of plots based on the object class using S3.
Maintained by Julia Wrobel. Last updated 1 years ago.
4 stars 4.91 score 45 scripts
sebdejean
CCA:Canonical Correlation Analysis
Provides a set of functions that extend the 'cancor' function with new numerical and graphical outputs. It also include a regularized extension of the canonical correlation analysis to deal with datasets with more variables than observations.
Maintained by Sรฉbastien Dรฉjean. Last updated 2 years ago.
4.85 score 334 scripts 3 dependents
cran
fds:Functional Data Sets
Functional data sets.
Maintained by Han Lin Shang. Last updated 6 years ago.
1 stars 4.79 score 148 dependentscran
rainbow:Bagplots, Boxplots and Rainbow Plots for Functional Data
Visualizing functional data and identifying functional outliers.
Maintained by Han Lin Shang. Last updated 1 years ago.
4.78 score 150 dependents
egarpor
goffda:Goodness-of-Fit Tests for Functional Data
Implementation of several goodness-of-fit tests for functional data. Currently, mostly related with the functional linear model with functional/scalar response and functional/scalar predictor. The package allows for the replication of the data applications considered in Garcรญa-Portuguรฉs, รlvarez-Liรฉbana, รlvarez-Pรฉrez and Gonzรกlez-Manteiga (2021) <doi:10.1111/sjos.12486>.
Maintained by Eduardo Garcรญa-Portuguรฉs. Last updated 1 years ago.
functional-data-analysisgoodness-of-fitreproducible-researchstatisticsopenblascpp
10 stars 4.76 score 19 scripts 1 dependentstrackerproject
trackeRapp:Interface for the Analysis of Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices
Provides an integrated user interface and workflow for the analysis of running, cycling and swimming data from GPS-enabled tracking devices through the 'trackeR' <https://CRAN.R-project.org/package=trackeR> R package.
Maintained by Ioannis Kosmidis. Last updated 3 years ago.
data-visualizationshinysports-appweb-appweb-development
32 stars 4.68 score 2 scriptscran
ftsa:Functional Time Series Analysis
Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.
Maintained by Han Lin Shang. Last updated 1 months ago.
6 stars 4.61 score 10 dependents
modal-inria
cfda:Categorical Functional Data Analysis
Package for the analysis of categorical functional data. The main purpose is to compute an encoding (real functional variable) for each state <doi:10.3390/math9233074>. It also provides functions to perform basic statistical analysis on categorical functional data.
Maintained by Quentin Grimonprez. Last updated 2 months ago.
categorical-datafunctional-data-analysishacktoberfest
4 stars 4.60 score 3 scripts
colemanrharris
mxnorm:Apply Normalization Methods to Multiplexed Images
Implements methods to normalize multiplexed imaging data, including statistical metrics and visualizations to quantify technical variation in this data type. Reference for methods listed here: Harris, C., Wrobel, J., & Vandekar, S. (2022). mxnorm: An R Package to Normalize Multiplexed Imaging Data. Journal of Open Source Software, 7(71), 4180, <doi:10.21105/joss.04180>.
Maintained by Coleman Harris. Last updated 2 years ago.
7 stars 4.54 score 7 scripts
tacazares
SeedMatchR:Find Matches to Canonical SiRNA Seeds in Genomic Features
On-target gene knockdown using siRNA ideally results from binding fully complementary regions in mRNA transcripts to induce cleavage. Off-target siRNA gene knockdown can occur through several modes, one being a seed-mediated mechanism mimicking miRNA gene regulation. Seed-mediated off-target effects occur when the ~8 nucleotides at the 5โ end of the guide strand, called a seed region, bind the 3โ untranslated regions of mRNA, causing reduced translation. Experiments using siRNA knockdown paired with RNA-seq can be used to detect siRNA sequences with potential off-target effects driven by the seed region. 'SeedMatchR' provides tools for exploring and detecting potential seed-mediated off-target effects of siRNA in RNA-seq experiments. 'SeedMatchR' is designed to extend current differential expression analysis tools, such as 'DESeq2', by annotating results with predicted seed matches. Using publicly available data, we demonstrate the ability of 'SeedMatchR' to detect cumulative changes in differential gene expression attributed to siRNA seed regions.
Maintained by Tareian Cazares. Last updated 1 years ago.
deseq2-analysismirnarna-seqsirnatranscriptomics
7 stars 4.54 score 7 scripts
ricgbl
etree:Classification and Regression with Structured and Mixed-Type Data
Implementation of Energy Trees, a statistical model to perform classification and regression with structured and mixed-type data. The model has a similar structure to Conditional Trees, but brings in Energy Statistics to test independence between variables that are possibly structured and of different nature. Currently, the package covers functions and graphs as structured covariates. It builds upon 'partykit' to provide functionalities for fitting, printing, plotting, and predicting with Energy Trees. Energy Trees are described in Giubilei et al. (2022) <arXiv:2207.04430>.
Maintained by Riccardo Giubilei. Last updated 3 years ago.
3 stars 4.52 score 11 scripts
raysinensis
colorrepel:Repel Visually Similar Colors for Colorblind Users in Various Plots
Iterate and repel visually similar colors away in various 'ggplot2' plots. When many groups are plotted at the same time on multiple axes, for instance stacked bars or scatter plots, effectively ordering colors becomes difficult. This tool iterates through color combinations to find the best solution to maximize visual distinctness of nearby groups, so plots are more friendly toward colorblind users. This is achieved by two distance measurements, distance between groups within the plot, and CIELAB color space distances between colors as described in Carter et al., (2018) <doi:10.25039/TR.015.2018>.
Maintained by Rui Fu. Last updated 2 months ago.
10 stars 4.48 score 1 scripts
alex-haixuw
pCODE:Estimation of an Ordinary Differential Equation Model by Parameter Cascade Method
An implementation of the parameter cascade method Ramsay, J. O., Hooker,G., Campbell, D., and Cao, J. (2007) <doi:10.1111/j.1467-9868.2007.00610.x> for estimating ordinary differential equation models with missing or complete observations. It combines smoothing method and profile estimation to estimate any non-linear dynamic system. The package also offers variance estimates for parameters of interest based on either bootstrap or Delta method.
Maintained by Haixu Wang. Last updated 3 years ago.
3 stars 4.48 score 6 scripts
jrvanderdoes
funkycells:Functional Data Analysis for Multiplexed Cell Images
Compare variables of interest between (potentially large numbers of) spatial interactions and meta-variables. Spatial variables are summarized using K, or other, functions, and projected for use in a modified random forest model. The model allows comparison of functional and non-functional variables to each other and to noise, giving statistical significance to the results. Included are preparation, modeling, and interpreting tools along with example datasets, as described in VanderDoes et al., (2023) <doi:10.1101/2023.07.18.549619>.
Maintained by Jeremy VanderDoes. Last updated 2 years ago.
1 stars 4.44 score 11 scripts
haghbinh
Rfssa:Functional Singular Spectrum Analysis
Methods and tools for implementing functional singular spectrum analysis and related techniques.
Maintained by Hossein Haghbin. Last updated 1 years ago.
7 stars 4.30 score 19 scripts
kisungyou
T4cluster:Tools for Cluster Analysis
Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.
Maintained by Kisung You. Last updated 4 years ago.
6 stars 4.26 score 9 scripts 2 dependents
bioc
PING:Probabilistic inference for Nucleosome Positioning with MNase-based or Sonicated Short-read Data
Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach.
Maintained by Renan Sauteraud. Last updated 4 days ago.
clusteringstatisticalmethodvisualizationsequencinggsl
4.18 score 7 scripts
alexvolkmann
MJMbamlss:Multivariate Joint Models with 'bamlss'
Multivariate joint models of longitudinal and time-to-event data based on functional principal components implemented with 'bamlss'. Implementation for Volkmann, Umlauf, Greven (2023) <arXiv:2311.06409>.
Maintained by Alexander Volkmann. Last updated 22 days ago.
2 stars 4.08 score 15 scriptsjrvanderdoes
fChange:Functional Change Point Detection and Analysis
Analyze functional data and its change points. Includes functionality to store and process data, summarize and validate assumptions, characterize and perform inference of change points, and provide visualizations. Data is stored as discretely collected observations without requiring the selection of basis functions. For more details see chapter 8 of Horvath and Rice (2024) <doi:10.1007/978-3-031-51609-2>. Additional papers are forthcoming. Focused works are also included in the documentation of corresponding functions.
Maintained by Jeremy VanderDoes. Last updated 20 hours ago.
1 stars 4.04 score
jeksterslab
bootStateSpace:Bootstrap for State Space Models
Provides a streamlined and user-friendly framework for bootstrapping in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. For an introduction to state space models in social and behavioral sciences, refer to Chow, Ho, Hamaker, and Dolan (2010) <doi:10.1080/10705511003661553>.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 1 months ago.
4.01 score 51 scriptsbioc
fCCAC:functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasets
Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomics, as it allows both to evaluate reproducibility of replicates, and to compare different datasets to identify potential correlations. fCCAC applies functional Canonical Correlation Analysis to allow the assessment of: (i) reproducibility of biological or technical replicates, analyzing their shared covariance in higher order components; and (ii) the associations between different datasets. fCCAC represents a more sophisticated approach that complements Pearson correlation of genomic coverage.
Maintained by Pedro Madrigal. Last updated 5 months ago.
epigeneticstranscriptionsequencingcoveragechipseqfunctionalgenomicsrnaseqatacseqmnaseseq
4.00 score 1 scriptsbioc
flowVS:Variance stabilization in flow cytometry (and microarrays)
Per-channel variance stabilization from a collection of flow cytometry samples by Bertlett test for homogeneity of variances. The approach is applicable to microarrays data as well.
Maintained by Ariful Azad. Last updated 5 months ago.
immunooncologyflowcytometrycellbasedassaysmicroarray
3.82 score 11 scripts
gpfda
GPFDA:Gaussian Process for Functional Data Analysis
Functionalities for modelling functional data with multidimensional inputs, multivariate functional data, and non-separable and/or non-stationary covariance structure of function-valued processes. In addition, there are functionalities for functional regression models where the mean function depends on scalar and/or functional covariates and the covariance structure depends on functional covariates. The development version of the package can be found on <https://github.com/gpfda/GPFDA-dev>.
Maintained by Evandro Konzen. Last updated 2 years ago.
1 stars 3.81 score 36 scripts 1 dependents
dennisprangle
gk:g-and-k and g-and-h Distribution Functions
Functions for the g-and-k and generalised g-and-h distributions.
Maintained by Dennis Prangle. Last updated 2 years ago.
5 stars 3.72 score 21 scripts
vinhtantran
puls:Partitioning Using Local Subregions
A method of clustering functional data using subregion information of the curves. It is intended to supplement the 'fda' and 'fda.usc' packages in functional data object clustering. It also facilitates the printing and plotting of the results in a tree format and limits the partitioning candidates into a specific set of subregions.
Maintained by Tan Tran. Last updated 4 years ago.
clusteringfunctional-data-analysismonothetic
3.70 score 4 scripts
mpff
elastes:Elastic Full Procrustes Means for Sparse and Irregular Planar Curves
Provides functions for the computation of functional elastic shape means over sets of open planar curves. The package is particularly suitable for settings where these curves are only sparsely and irregularly observed. It uses a novel approach for elastic shape mean estimation, where planar curves are treated as complex functions and a full Procrustes mean is estimated from the corresponding smoothed Hermitian covariance surface. This is combined with the methods for elastic mean estimation proposed in Steyer, Stรถcker, Greven (2022) <doi:10.1111/biom.13706>. See Stรถcker et. al. (2022) <arXiv:2203.10522> for details.
Maintained by Manuel Pfeuffer. Last updated 2 years ago.
1 stars 3.70 score 7 scripts
kangjian2016
brainKCCA:Region-Level Connectivity Network Construction via Kernel Canonical Correlation Analysis
It is designed to calculate connection between (among) brain regions and plot connection lines. Also, the summary function is included to summarize group-level connectivity network. Kang, Jian (2016) <doi:10.1016/j.neuroimage.2016.06.042>.
Maintained by Jian Kang. Last updated 6 years ago.
3.70 score 5 scriptskisungyou
Riemann:Learning with Data on Riemannian Manifolds
We provide a variety of algorithms for manifold-valued data, including Frรฉchet summaries, hypothesis testing, clustering, visualization, and other learning tasks. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> for general exposition to statistics on manifolds.
Maintained by Kisung You. Last updated 2 years ago.
10 stars 3.70 score 8 scripts
drg-123
NSM3:Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition
Designed to replace the tables which were in the back of the first two editions of Hollander and Wolfe - Nonparametric Statistical Methods. Exact procedures are performed when computationally possible. Monte Carlo and Asymptotic procedures are performed otherwise. For those procedures included in the base packages, our code simply provides a wrapper to standardize the output with the other procedures in the package.
Maintained by Grant Schneider. Last updated 5 months ago.
1 stars 3.67 score 115 scripts 1 dependents
gmestrem
fdaACF:Autocorrelation Function for Functional Time Series
Quantify the serial correlation across lags of a given functional time series using the autocorrelation function and a partial autocorrelation function for functional time series proposed in Mestre et al. (2021) <doi:10.1016/j.csda.2020.107108>. The autocorrelation functions are based on the L2 norm of the lagged covariance operators of the series. Functions are available for estimating the distribution of the autocorrelation functions under the assumption of strong functional white noise.
Maintained by Guillermo Mestre Marcos. Last updated 4 years ago.
8 stars 3.64 score 11 scripts
bfontez
DrBats:Data Representation: Bayesian Approach That's Sparse
Feed longitudinal data into a Bayesian Latent Factor Model to obtain a low-rank representation. Parameters are estimated using a Hamiltonian Monte Carlo algorithm with STAN. See G. Weinrott, B. Fontez, N. Hilgert and S. Holmes, "Bayesian Latent Factor Model for Functional Data Analysis", Actes des JdS 2016.
Maintained by Benedicte Fontez. Last updated 3 years ago.
1 stars 3.51 score 13 scripts
pauleilers
JOPS:Practical Smoothing with P-Splines
Functions and data to reproduce all plots in the book "Practical Smoothing. The Joys of P-splines" by Paul H.C. Eilers and Brian D. Marx (2021, ISBN:978-1108482950).
Maintained by Paul Eilers. Last updated 2 years ago.
1 stars 3.43 score 296 scripts 3 dependents
r-forge
anacor:Simple and Canonical Correspondence Analysis
Performs simple and canonical CA (covariates on rows/columns) on a two-way frequency table (with missings) by means of SVD. Different scaling methods (standard, centroid, Benzecri, Goodman) as well as various plots including confidence ellipsoids are provided.
Maintained by Patrick Mair. Last updated 5 days ago.
3.40 score 21 scriptshaghbinh
Rsfar:Seasonal Functional Autoregressive Models
This is a collection of functions designed for simulating, estimating and forecasting seasonal functional autoregressive time series of order one. These methods are addressed in the manuscript: <https://www.monash.edu/business/ebs/research/publications/ebs/wp16-2019.pdf>.
Maintained by Hossein Haghbin. Last updated 4 years ago.
5 stars 3.40 scorecran
meboot:Maximum Entropy Bootstrap for Time Series
Maximum entropy density based dependent data bootstrap. An algorithm is provided to create a population of time series (ensemble) without assuming stationarity. The reference paper (Vinod, H.D., 2004 <DOI: 10.1016/j.jempfin.2003.06.002>) explains how the algorithm satisfies the ergodic theorem and the central limit theorem.
Maintained by Fred Viole. Last updated 2 years ago.
2 stars 3.38 score 2 dependents
jorgetendeiro
PerFit:Person Fit
Several person-fit statistics (PFSs; Meijer and Sijtsma, 2001, <doi:10.1177/01466210122031957>) are offered. These statistics allow assessing whether individual response patterns to tests or questionnaires are (im)plausible given the other respondents in the sample or given a specified item response theory model. Some PFSs apply to dichotomous data, such as the likelihood-based PFSs (lz, lz*) and the group-based PFSs (personal biserial correlation, caution index, (normed) number of Guttman errors, agreement/disagreement/dependability statistics, U3, ZU3, NCI, Ht). PFSs suitable to polytomous data include extensions of lz, U3, and (normed) number of Guttman errors.
Maintained by Jorge N. Tendeiro. Last updated 3 years ago.
1 stars 3.36 score 46 scriptsbioc
FRGEpistasis:Epistasis Analysis for Quantitative Traits by Functional Regression Model
A Tool for Epistasis Analysis Based on Functional Regression Model
Maintained by Futao Zhang. Last updated 5 months ago.
geneticsnetworkinferencegeneticvariabilitysoftware
3.30 score 6 scriptsbioc
IWTomics:Interval-Wise Testing for Omics Data
Implementation of the Interval-Wise Testing (IWT) for omics data. This inferential procedure tests for differences in "Omics" data between two groups of genomic regions (or between a group of genomic regions and a reference center of symmetry), and does not require fixing location and scale at the outset.
Maintained by Marzia A Cremona. Last updated 5 months ago.
statisticalmethodmultiplecomparisondifferentialexpressiondifferentialmethylationdifferentialpeakcallinggenomeannotationdataimport
3.30 score 5 scripts
unina-sfere
adass:Adaptive Smoothing Spline (AdaSS) Estimator for the Function-on-Function Linear Regression
Implements the adaptive smoothing spline estimator for the function-on-function linear regression model described in Centofanti et al. (2023) <doi:10.1007/s00180-022-01223-6>.
Maintained by Fabio Centofanti. Last updated 9 months ago.
2 stars 3.30 score 20 scripts
jcai-1122
DGP4LCF:Dependent Gaussian Processes for Longitudinal Correlated Factors
Model high-dimensional gene expression trajectories using dynamic factor analysis with dependent Gaussian processes
Maintained by Jiachen Cai. Last updated 10 months ago.
3.30 score 3 scripts
ls-git-17
fdANOVA:Analysis of Variance for Univariate and Multivariate Functional Data
Performs analysis of variance testing procedures for univariate and multivariate functional data (Cuesta-Albertos and Febrero-Bande (2010) <doi:10.1007/s11749-010-0185-3>, Gorecki and Smaga (2015) <doi:10.1007/s00180-015-0555-0>, Gorecki and Smaga (2017) <doi:10.1080/02664763.2016.1247791>, Zhang et al. (2018) <doi:10.1016/j.csda.2018.05.004>).
Maintained by Lukasz Smaga. Last updated 7 years ago.
3 stars 3.23 score 28 scriptsunina-sfere
rofanova:Robust Functional Analysis of Variance
Implements the robust functional analysis of variance (RoFANOVA), described in Centofanti et al. (2021) <arXiv:2112.10643>. It allows testing mean differences among groups of functional data by being robust against the presence of outliers.
Maintained by Fabio Centofanti. Last updated 3 years ago.
3.22 score 11 scripts 1 dependents
b-thi
FuncNN:Functional Neural Networks
A collection of functions which fit functional neural network models. In other words, this package will allow users to build deep learning models that have either functional or scalar responses paired with functional and scalar covariates. We implement the theoretical discussion found in Thind, Multani and Cao (2020) <arXiv:2006.09590> through the help of a main fitting and prediction function as well as a number of helper functions to assist with cross-validation, tuning, and the display of estimated functional weights.
Maintained by Barinder Thind. Last updated 5 years ago.
3 stars 3.18 score 5 scripts
kuan-cheng-da
EATME:EWMA-p control charts with correction of measurement error
The package EATME, refered to EWMA with Adjustments To Measuremeant Error, aims to address measurement error effects when constructing EWMA-p control charts. The method primarily focuses on binary random variables, but it can be applied to any continuous random variables by using sign statistic to transform them to discrete ones. With the correction of measurement error effects, we can obtain the corrected control limits of EWMA-p control chart and reasonably adjusted EWMA-p control charts.
Maintained by Cheng-Kuan Lin. Last updated 11 months ago.
3.18 score 1 scripts
nenuial
geographer:Geography Vizualisations
Provides function and objects to establish vizualisations for my Geography lessons.
Maintained by Pascal Burkhard. Last updated 1 months ago.
2 stars 3.08 score
marcvidalbadia
pfica:Independent Components Analysis Techniques for Functional Data
This package includes a set of tools to perform smoothed (and non-smoothed) principal/independent components analysis of functional data. Various functional pre-whitening approaches are implemented as discussed in Vidal and Aguilera (2022) โNovel whitening approaches in functional settings", <doi:10.1002/sta4.516>. Further whitening representations of functional data can be derived in terms of a few principal components, providing a powerful avenue to explore hidden structures in low dimensional settings: see Vidal, Rosso and Aguilera (2021) โBi-smoothed functional independent component analysis for EEG artifact removalโ, <doi:10.3390/math9111243>.
Maintained by Marc Vidal. Last updated 2 years ago.
b-splinesfobiicakurtosispenalization
2 stars 3.00 score 3 scripts
liukf10
DDPNA:Disease-Drived Differential Proteins Co-Expression Network Analysis
Functions designed to connect disease-related differential proteins and co-expression network. It provides the basic statics analysis included t test, ANOVA analysis. The network construction is not offered by the package, you can used 'WGCNA' package which you can learn in Peter et al. (2008) <doi:10.1186/1471-2105-9-559>. It also provides module analysis included PCA analysis, two enrichment analysis, Planner maximally filtered graph extraction and hub analysis.
Maintained by Kefu Liu. Last updated 4 years ago.
2 stars 3.00 score 4 scriptsalexvolkmann
multifamm:Multivariate Functional Additive Mixed Models
An implementation for multivariate functional additive mixed models (multiFAMM), see Volkmann et al. (2021, <arXiv:2103.06606>). It builds on developed methods for univariate sparse functional regression models and multivariate functional principal component analysis. This package contains the function to run a multiFAMM and some convenience functions useful when working with large models. An additional package on GitHub contains more convenience functions to reproduce the analyses of the corresponding paper (alexvolkmann/multifammPaper).
Maintained by Alexander Volkmann. Last updated 4 years ago.
2 stars 3.00 score 10 scripts
rempsyc
pubmedDashboard:Creating PubMed Data Visualization Dashboards
Package to facilitate the creation of data visualization dashboards through the flexdashboard and easyPubMed packages. This package is now deprecated in favour of the pubDashboard package.
Maintained by Rรฉmi Thรฉriault. Last updated 10 months ago.
4 stars 2.90 score 6 scripts
radivot
SEERaBomb:SEER and Atomic Bomb Survivor Data Analysis Tools
Creates SEER (Surveillance, Epidemiology and End Results) and A-bomb data binaries from ASCII sources and provides tools for estimating SEER second cancer risks. Methods are described in <doi:10.1038/leu.2015.258>.
Maintained by Tomas Radivoyevitch. Last updated 5 years ago.
2.85 score 176 scriptsunina-sfere
slasso:S-LASSO Estimator for the Function-on-Function Linear Regression
Implements the smooth LASSO estimator for the function-on-function linear regression model described in Centofanti et al. (2020) <arXiv:2007.00529>.
Maintained by Fabio Centofanti. Last updated 3 years ago.
1 stars 2.74 score 11 scripts
aparamon
mar1s:Multiplicative AR(1) with Seasonal Processes
Multiplicative AR(1) with Seasonal is a stochastic process model built on top of AR(1). The package provides the following procedures for MAR(1)S processes: fit, compose, decompose, advanced simulate and predict.
Maintained by Andrey Paramonov. Last updated 7 years ago.
2.70 score 8 scripts
asgari-fatemeh
dfrr:Dichotomized Functional Response Regression
Implementing Function-on-Scalar Regression model in which the response function is dichotomized and observed sparsely. This package provides smooth estimations of functional regression coefficients and principal components for the dfrr model.
Maintained by Fatemeh Asgari. Last updated 5 years ago.
1 stars 2.70 score
mohmedsoudy
ggaligner:Visualizing Sequence Alignment by Generating Publication-Ready Plots
Providing publication-ready graphs for Multiple sequence alignment. Moreover, it provides a unique solution for visualizing the multiple sequence alignment without the need to do the alignment in each run which is a big limitation in other available packages.
Maintained by Mohamed Soudy. Last updated 2 years ago.
2.70 score 1 scripts
hughjonesd
truelies:Bayesian Methods to Estimate the Proportion of Liars in Coin Flip Experiments
Implements Bayesian methods, described in Hugh-Jones (2019) <doi:10.1007/s40881-019-00069-x>, for estimating the proportion of liars in coin flip-style experiments, where subjects report a random outcome and are paid for reporting a "good" outcome.
Maintained by David Hugh-Jones. Last updated 4 years ago.
2.70 score 2 scriptsunina-sfere
sasfunclust:Sparse and Smooth Functional Clustering
Implements the sparse and smooth functional clustering (SaS-Funclust) method (Centofanti et al. (2021) <arXiv:2103.15224>) that aims to classify a sample of curves into homogeneous groups while jointly detecting the most informative portions of domain.
Maintained by Fabio Centofanti. Last updated 4 years ago.
1 stars 2.70 score 9 scriptsjamesramsay5
TestGardener:Information Analysis for Test and Rating Scale Data
Develop, evaluate, and score multiple choice examinations, psychological scales, questionnaires, and similar types of data involving sequences of choices among one or more sets of answers. This version of the package should be considered as brand new. Almost all of the functions have been changed, including their argument list. See the file NEWS.Rd in the Inst folder for more information. Using the package does not require any formal statistical knowledge beyond what would be provided by a first course in statistics in a social science department. There the user would encounter the concept of probability and how it is used to model data and make decisions, and would become familiar with basic mathematical and statistical notation. Most of the output is in graphical form.
Maintained by James Ramsay. Last updated 1 years ago.
1 stars 2.70 score 5 scripts
mingsnu
stfit:Spatio-Temporal Functional Imputation Tool
A general spatiotemporal satellite image imputation method based on sparse functional data analytic techniques. The imputation method applies and extends the Functional Principal Analysis by Conditional Estimation (PACE). The underlying idea for the proposed procedure is to impute a missing pixel by borrowing information from temporally and spatially contiguous pixels based on the best linear unbiased prediction.
Maintained by Weicheng Zhu. Last updated 2 years ago.
2.61 score 41 scriptsnenuial
geovizr:Support for Knitr (Quarto/Rmd)
Provide support functions for Quarto and Rmd documents.
Maintained by Pascal Burkhard. Last updated 1 months ago.
2.60 score 3 scripts
jihx1015
MECfda:Scalar-on-Function Regression with Measurement Error Correction
Solve scalar-on-function linear models, including generalized linear mixed effect model and quantile linear regression model, and bias correction estimation methods due to measurement error. Details about the measurement error bias correction methods, see Luan et al. (2023) <doi:10.48550/arXiv.2305.12624>, Tekwe et al. (2022) <doi:10.1093/biostatistics/kxac017>, Zhang et al. (2023) <doi:10.5705/ss.202021.0246>, Tekwe et al. (2019) <doi:10.1002/sim.8179>.
Maintained by Heyang Ji. Last updated 23 days ago.
1 stars 2.30 score 1 scriptsrobjhyndman
addb:Australian Demographic Data Bank
These data are from the Australian Demographic Data Bank. They can be plotted and analysed using the demography package.
Maintained by Rob Hyndman. Last updated 2 years ago.
4 stars 2.30 scorekisungyou
TDAkit:Toolkit for Topological Data Analysis
Topological data analysis studies structure and shape of the data using topological features. We provide a variety of algorithms to learn with persistent homology of the data based on functional summaries for clustering, hypothesis testing, visualization, and others. We refer to Wasserman (2018) <doi:10.1146/annurev-statistics-031017-100045> for a statistical perspective on the topic.
Maintained by Kisung You. Last updated 4 years ago.
2 stars 2.30 score 4 scriptscran
sparseFLMM:Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data
Estimation of functional linear mixed models for irregularly or sparsely sampled data based on functional principal component analysis.
Maintained by Jona Cederbaum. Last updated 4 years ago.
2.26 score 6 dependents
chrschellhase
pendensity:Density Estimation with a Penalized Mixture Approach
Estimation of univariate (conditional) densities using penalized B-splines with automatic selection of optimal smoothing parameter.
Maintained by Christian Schellhase. Last updated 6 years ago.
2.00 score 2 scriptscran
glober:Estimating Functions with Multivariate B-Splines
Generalized LassO applied to knot selection in multivariate B-splinE Regression (GLOBER) implements a novel approach for estimating functions in a multivariate nonparametric regression model based on an adaptive knot selection for B-splines using the Generalized Lasso. For further details we refer the reader to the paper Savino, M. E. and Lรฉvy-Leduc, C. (2023), <arXiv:2306.00686>.
Maintained by Mary E. Savino. Last updated 2 years ago.
2.00 score
ivanfernandezval
quantreg.nonpar:Nonparametric Series Quantile Regression
Implements the nonparametric quantile regression method developed by Belloni, Chernozhukov, and Fernandez-Val (2011) to partially linear quantile models. Provides point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. Provides pointwise and uniform confidence intervals using analytic and resampling methods.
Maintained by Ivan Fernandez-Val. Last updated 9 years ago.
2.00 score 4 scriptsgloewing
studyStrap:Study Strap and Multi-Study Learning Algorithms
Implements multi-study learning algorithms such as merging, the study-specific ensemble (trained-on-observed-studies ensemble) the study strap, the covariate-matched study strap, covariate-profile similarity weighting, and stacking weights. Embedded within the 'caret' framework, this package allows for a wide range of single-study learners (e.g., neural networks, lasso, random forests). The package offers over 20 default similarity measures and allows for specification of custom similarity measures for covariate-profile similarity weighting and an accept/reject step. This implements methods described in Loewinger, Kishida, Patil, and Parmigiani. (2019) <doi:10.1101/856385>.
Maintained by Gabriel Loewinger. Last updated 5 years ago.
2.00 score 2 scriptscran
absorber:Variable Selection in Nonparametric Models using B-Splines
A variable selection method using B-Splines in multivariate nOnparametric Regression models Based on partial dErivatives Regularization (ABSORBER) implements a novel variable selection method in a nonlinear multivariate model using B-splines. For further details we refer the reader to the paper Savino, M. E. and Lรฉvy-Leduc, C. (2024), <https://hal.science/hal-04434820>.
Maintained by Mary E. Savino. Last updated 1 years ago.
2.00 scorecran
sft:Functions for Systems Factorial Technology Analysis of Data
A series of tools for analyzing Systems Factorial Technology data. This includes functions for plotting and statistically testing capacity coefficient functions and survivor interaction contrast functions. Houpt, Blaha, McIntire, Havig, and Townsend (2013) <doi:10.3758/s13428-013-0377-3> provide a basic introduction to Systems Factorial Technology along with examples using the sft R package.
Maintained by Joe Houpt. Last updated 7 years ago.
1 stars 2.00 score
hamedhm
BDWreg:Bayesian Inference for Discrete Weibull Regression
A Bayesian regression model for discrete response, where the conditional distribution is modelled via a discrete Weibull distribution. This package provides an implementation of Metropolis-Hastings and Reversible-Jumps algorithms to draw samples from the posterior. It covers a wide range of regularizations through any two parameter prior. Examples are Laplace (Lasso), Gaussian (ridge), Uniform, Cauchy and customized priors like a mixture of priors. An extensive visual toolbox is included to check the validity of the results as well as several measures of goodness-of-fit.
Maintained by Hamed Haselimashhadi. Last updated 8 years ago.
2.00 score 4 scripts
mattwand
curvHDR:Filtering of Flow Cytometry Samples
Filtering, also known as gating, of flow cytometry samples using the curvHDR method, which is described in Naumann, U., Luta, G. and Wand, M.P. (2010) <DOI:10.1186/1471-2105-11-44>.
Maintained by Matt Wand. Last updated 2 years ago.
2.00 score 6 scripts
xdaiisu
TE:Insertion/Deletion Dynamics for Transposable Elements
Provides functions to estimate the insertion and deletion rates of transposable element (TE) families. The estimation of insertion rate consists of an improved estimate of the age distribution that takes into account random mutations, and an adjustment by the deletion rate. A hypothesis test for a uniform insertion rate is also implemented. This package implements the methods proposed in Dai et al (2018).
Maintained by Xiongtao Dai. Last updated 7 years ago.
2.00 score 7 scripts
ehanks
ctmcmove:Modeling Animal Movement with Continuous-Time Discrete-Space Markov Chains
Software to facilitates taking movement data in xyt format and pairing it with raster covariates within a continuous time Markov chain (CTMC) framework. As described in Hanks et al. (2015) <DOI:10.1214/14-AOAS803> , this allows flexible modeling of movement in response to covariates (or covariate gradients) with model fitting possible within a Poisson GLM framework.
Maintained by Ephraim Hanks. Last updated 3 months ago.
1 stars 1.78 score 30 scriptsdrg-123
IIS:Datasets to Accompany Wolfe and Schneider - Intuitive Introductory Statistics
These datasets and functions accompany Wolfe and Schneider (2017) - Intuitive Introductory Statistics (ISBN: 978-3-319-56070-0) <doi:10.1007/978-3-319-56072-4>. They are used in the examples throughout the text and in the end-of-chapter exercises. The datasets are meant to cover a broad range of topics in order to appeal to the diverse set of interests and backgrounds typically present in an introductory Statistics class.
Maintained by Grant Schneider. Last updated 2 months ago.
1.74 score 55 scriptscran
popstudy:Applied Techniques to Demographic and Time Series Analysis
The use of overparameterization is proposed with combinatorial analysis to test a broader spectrum of possible ARIMA models. In the selection of ARIMA models, the most traditional methods such as correlograms or others, do not usually cover many alternatives to define the number of coefficients to be estimated in the model, which represents an estimation method that is not the best. The popstudy package contains several tools for statistical analysis in demography and time series based in Shryock research (Shryock et. al. (1980) <https://books.google.co.cr/books?id=8Oo6AQAAMAAJ>).
Maintained by Cesar Gamboa-Sanabria. Last updated 1 years ago.
1.70 scorecran
pcdpca:Dynamic Principal Components for Periodically Correlated Functional Time Series
Method extends multivariate and functional dynamic principal components to periodically correlated multivariate time series. This package allows you to compute true dynamic principal components in the presence of periodicity. We follow implementation guidelines as described in Kidzinski, Kokoszka and Jouzdani (2017), in Principal component analysis of periodically correlated functional time series <arXiv:1612.00040>.
Maintained by Lukasz Kidzinski. Last updated 8 years ago.
1.70 score
cran
mixedsde:Estimation Methods for Stochastic Differential Mixed Effects Models
Inference on stochastic differential models Ornstein-Uhlenbeck or Cox-Ingersoll-Ross, with one or two random effects in the drift function.
Maintained by Charlotte Dion. Last updated 6 years ago.
1.70 scorecran
SCCS:The Self-Controlled Case Series Method
Various self-controlled case series models used to investigate associations between time-varying exposures such as vaccines or other drugs or non drug exposures and an adverse event can be fitted. Detailed information on the self-controlled case series method and its extensions with more examples can be found in Farrington, P., Whitaker, H., and Ghebremichael Weldeselassie, Y. (2018, ISBN: 978-1-4987-8159-6. Self-controlled Case Series studies: A modelling Guide with R. Boca Raton: Chapman & Hall/CRC Press) and <https://sccs-studies.info/index.html>.
Maintained by "Yonas Ghebremichael Weldeselassie". Last updated 12 months ago.
1.60 score
gileshooker
CollocInfer:Collocation Inference for Dynamic Systems
These functions implement collocation-inference for continuous-time and discrete-time stochastic processes. They provide model-based smoothing, gradient-matching, generalized profiling and forwards prediction error methods.
Maintained by Giles Hooker. Last updated 5 months ago.
1 stars 1.51 score 32 scriptscran
funFEM:Clustering in the Discriminative Functional Subspace
The funFEM algorithm (Bouveyron et al., 2014) allows to cluster functional data by modeling the curves within a common and discriminative functional subspace.
Maintained by Charles Bouveyron. Last updated 3 years ago.
1.48 score 1 dependentscran
DWreg:Parametric Regression for Discrete Response
Regression for a discrete response, where the conditional distribution is modelled via a discrete Weibull distribution.
Maintained by Veronica Vinciotti. Last updated 9 years ago.
1.48 score 1 dependents
philippe-a
RChronoModel:Post-Processing of the Markov Chain Simulated by ChronoModel or Oxcal
Provides a list of functions for the statistical analysis and the post-processing of the Markov Chains simulated by ChronoModel (see <http://www.chronomodel.fr> for more information). ChronoModel is a friendly software to construct a chronological model in a Bayesian framework. Its output is a sampled Markov chain from the posterior distribution of dates component the chronology. The functions can also be applied to the analyse of mcmc output generated by Oxcal software.
Maintained by Anne Philippe. Last updated 8 years ago.
1.43 score 27 scripts
paolo-vergo
conformalInference.fd:Tools for Conformal Inference for Regression in Multivariate Functional Setting
It computes full conformal, split conformal and multi split conformal prediction regions when the response has functional nature. Moreover, the package also contain a plot function to visualize the output of the split conformal. To guarantee consistency, the package structure mimics the univariate 'conformalInference' package of professor Ryan Tibshirani. The main references for the code are: Diquigiovanni, Fontana, and Vantini (2021) <arXiv:2102.06746>, Diquigiovanni, Fontana, and Vantini (2021) <arXiv:2106.01792>, Solari, and Djordjilovic (2021) <arXiv:2103.00627>.
Maintained by Paolo Vergottini. Last updated 3 years ago.
1.36 score 23 scripts
mlaib
FiSh:Fisher-Shannon Method
Proposes non-parametric estimates of the Fisher information measure and the Shannon entropy power. More theoretical and implementation details can be found in Guignard et al. <doi:10.3389/feart.2020.00255>. A 'python' version of this work is available on 'github' and 'PyPi' ('FiShPy').
Maintained by Mohamed Laib. Last updated 4 years ago.
1.30 score
hwj0828
CSTE:Covariate Specific Treatment Effect (CSTE) Curve
A uniform statistical inferential tool in making individualized treatment decisions, which implements the methods of Ma et al. (2017)<DOI:10.1177/0962280214541724> and Guo et al. (2021)<DOI:10.1080/01621459.2020.1865167>. It uses a flexible semiparametric modeling strategy for heterogeneous treatment effect estimation in high-dimensional settings and can gave valid confidence bands. Based on it, one can find the subgroups of patients that benefit from each treatment, thereby making individualized treatment selection.
Maintained by Wenjie Hu. Last updated 4 months ago.
1.30 score 1 scripts
haoluns
PFLR:Estimating Penalized Functional Linear Regression
Implementation of commonly used penalized functional linear regression models, including the Smooth and Locally Sparse (SLoS) method by Lin et al. (2016) <doi:10.1080/10618600.2016.1195273>, Nested Group bridge Regression (NGR) method by Guan et al. (2020) <doi:10.1080/10618600.2020.1713797>, Functional Linear Regression That's interpretable (FLIRTI) by James et al. (2009) <doi:10.1214/08-AOS641>, and the Penalized B-spline regression method.
Maintained by Haolun Shi. Last updated 7 months ago.
1.30 score
arolluom
RcmdrPlugin.RiskDemo:R Commander Plug-in for Risk Demonstration
R Commander plug-in to demonstrate various actuarial and financial risks. It includes valuation of bonds and stocks, portfolio optimization, classical ruin theory, demography and epidemic.
Maintained by Arto Luoma. Last updated 1 years ago.
1.30 score 20 scriptscran
nsROC:Non-Standard ROC Curve Analysis
Tools for estimating Receiver Operating Characteristic (ROC) curves, building confidence bands, comparing several curves both for dependent and independent data, estimating the cumulative-dynamic ROC curve in presence of censored data, and performing meta-analysis studies, among others.
Maintained by Sonia Perez Fernandez. Last updated 7 years ago.
1 stars 1.30 scorecran
sicure:Single-Index Mixture Cure Models
Single-index mixture cure models allow estimating the probability of cure and the latency depending on a vector (or functional) covariate, avoiding the curse of dimensionality. The vector of parameters that defines the model can be estimated by maximum likelihood. A nonparametric estimator for the conditional density of the susceptible population is provided. For more details, see Piรฑeiro-Lamas (2024) (<https://ruc.udc.es/dspace/handle/2183/37035>).
Maintained by Beatriz Piรฑeiro-Lamas. Last updated 5 months ago.
1.00 scorecran
FADPclust:Functional Data Clustering Using Adaptive Density Peak Detection
An implementation of a clustering algorithm for functional data based on adaptive density peak detection technique, in which the density is estimated by functional k-nearest neighbor density estimation based on a proposed semi-metric between functions. The proposed functional data clustering algorithm is computationally fast since it does not need iterative process. (Alex Rodriguez and Alessandro Laio (2014) <doi:10.1126/science.1242072>; Xiao-Feng Wang and Yifan Xu (2016) <doi:10.1177/0962280215609948>).
Maintained by Rui Ren. Last updated 2 years ago.
1 stars 1.00 scorecran
nFunNN:Nonlinear Functional Principal Component Analysis using Neural Networks
Implementation for 'nFunNN' method, which is a novel nonlinear functional principal component analysis method using neural networks. The crucial function of this package is nFunNNmodel().
Maintained by Rou Zhong. Last updated 11 months ago.
1.00 scorels-git-17
multiFANOVA:Multiple Contrast Tests for Functional Data
The provided package implements multiple contrast tests for functional data (Munko et al., 2023, <arXiv:2306.15259>). These procedures enable us to evaluate the overall hypothesis regarding equality, as well as specific hypotheses defined by contrasts. In particular, we can perform post hoc tests to examine particular comparisons of interest. Different experimental designs are supported, e.g., one-way and multi-way analysis of variance for functional data.
Maintained by Lukasz Smaga. Last updated 2 years ago.
1.00 scorecran
pencopulaCond:Estimating Non-Simplified Vine Copulas Using Penalized Splines
Estimating Non-Simplified Vine Copulas Using Penalized Splines.
Maintained by Christian Schellhase. Last updated 8 years ago.
1 stars 1.00 score
eguidotti
yuimaGUI:A Graphical User Interface for the 'yuima' Package
Provides a graphical user interface for the 'yuima' package.
Maintained by Emanuele Guidotti. Last updated 3 years ago.
1.00 score 2 scriptscran
cvmaPLFAM:Cross-Validation Model Averaging for Partial Linear Functional Additive Models
Produce an averaging estimate/prediction by combining all candidate models for partial linear functional additive models, using multi-fold cross-validation criterion. More details can be referred to Shishi Liu and Jingxiao Zhang. (2021) <arXiv:2105.00966>.
Maintained by Shishi Liu. Last updated 2 years ago.
1.00 scorels-git-17
rmfanova:Repeated Measures Functional Analysis of Variance
The provided package implements the statistical tests for the functional repeated measures analysis problem (Kurylo and Smaga, 2023, <arXiv:2306.03883>). These procedures enable us to verify the overall hypothesis regarding equality, as well as hypotheses for pairwise comparisons (i.e., post hoc analysis) of mean functions corresponding to repeated experiments.
Maintained by Lukasz Smaga. Last updated 2 years ago.
1.00 score 2 scriptscran
SLFPCA:Sparse Logistic Functional Principal Component Analysis
Implementation for sparse logistic functional principal component analysis (SLFPCA). SLFPCA is specifically developed for functional binary data, and the estimated eigenfunction can be strictly zero on some sub-intervals, which is helpful for interpretation. The crucial function of this package is SLFPCA().
Maintained by Rou Zhong. Last updated 2 years ago.
1 stars 1.00 scorecran
warpMix:Mixed Effects Modeling with Warping for Functional Data Using B-Spline
Mixed effects modeling with warping for functional data using B- spline. Warping coefficients are considered as random effects, and warping functions are general functions, parameters representing the projection onto B- spline basis of a part of the warping functions. Warped data are modelled by a linear mixed effect functional model, the noise is Gaussian and independent from the warping functions.
Maintained by Emilie Devijver. Last updated 8 years ago.
1.00 scorecran
MRmediation:A Causal Mediation Method with Methylated Region (MR) as the Mediator
A causal mediation approach under the counterfactual framework to test the significance of total, direct and indirect effects. In this approach, a group of methylated sites from a predefined region are utilized as the mediator, and the functional transformation is used to reduce the possible high dimension in the region-based methylated sites and account for their location information.
Maintained by Qi Yan. Last updated 4 years ago.
1.00 score
lfrm
funpca:Functional Principal Component Analysis
Functional principal component analysis under the Linear Mixed Models representation of smoothing splines. The method utilizes the Demmler-Reinsch basis and assumes error independence. For more details see: F. Rosales (2016) <https://ediss.uni-goettingen.de/handle/11858/00-1735-0000-0028-87F9-6>.
Maintained by Francisco Rosales. Last updated 2 years ago.
1.00 score
emilielebarbier74
TrendTM:Trend of High-Dimensional Time Series Matrix Estimation
Matrix factorization for multivariate time series with both low rank and temporal structures. The procedure is the one proposed by Alquier, P. and Marie, N. "Matrix factorization for multivariate time series analysis." Electronic Journal of Statistics, 13(2), 4346-4366 (2019).
Maintained by Emilie Lebarbier. Last updated 2 days ago.
1.00 score 2 scripts
ufukbeyaztas
robflreg:Robust Functional Linear Regression
Functions for implementing robust methods for functional linear regression. In the functional linear regression, we consider scalar-on-function linear regression and function-on-function linear regression. More details, see Beyaztas, U., and Shang, H. L. (2021) <arXiv:2111.01238> and Beyaztas, U., and Shang, H. L. (2022) <arXiv:2203.05065>.
Maintained by Ufuk Beyaztas. Last updated 1 years ago.
1.00 score 8 scripts
gianluca-sottile
clustEff:Clusters of Effects Curves in Quantile Regression Models
Clustering method to cluster both effects curves, through quantile regression coefficient modeling, and curves in functional data analysis. Sottile G. and Adelfio G. (2019) <doi:10.1007/s00180-018-0817-8>.
Maintained by Gianluca Sottile. Last updated 1 years ago.
1.00 score 7 scriptscran
logitFD:Functional Principal Components Logistic Regression
Functions for fitting a functional principal components logit regression model in four different situations: ordinary and filtered functional principal components of functional predictors, included in the model according to their variability explanation power, and according to their prediction ability by stepwise methods. The proposed methods were developed in Escabias et al (2004) <doi:10.1080/10485250310001624738> and Escabias et al (2005) <doi:10.1016/j.csda.2005.03.011>.
Maintained by Manuel Escabias. Last updated 3 years ago.
1.00 scorecran
funLBM:Model-Based Co-Clustering of Functional Data
The funLBM algorithm allows to simultaneously cluster the rows and the columns of a data matrix where each entry of the matrix is a function or a time series.
Maintained by Charles Bouveyron. Last updated 3 years ago.
1.00 score
laylaparast
longsurr:Longitudinal Surrogate Marker Analysis
Assess the proportion of treatment effect explained by a longitudinal surrogate marker as described in Agniel D and Parast L (2021) <doi:10.1111/biom.13310>.
Maintained by Layla Parast. Last updated 3 years ago.
1.00 scorecran
freqdom.fda:Functional Time Series: Dynamic Functional Principal Components
Implementations of functional dynamic principle components analysis. Related graphic tools and frequency domain methods. These methods directly use multivariate dynamic principal components implementation, following the guidelines from Hormann, Kidzinski and Hallin (2016), Dynamic Functional Principal Component <doi:10.1111/rssb.12076>.
Maintained by Kidzinski L.. Last updated 3 years ago.
1.00 scorecran
mrct:Outlier Detection of Functional Data Based on the Minimum Regularized Covariance Trace Estimator
Detect outlying observations in functional data sets based on the minimum regularized covariance trace (MRCT) estimator. Includes implementation of Oguamalam et al. (2023) <arXiv:2307.13509>.
Maintained by Jeremy Oguamalam. Last updated 2 years ago.
1.00 scorecran
hdftsa:High-Dimensional Functional Time Series Analysis
Offers methods for visualizing, modelling, and forecasting high-dimensional functional time series, also known as functional panel data. Documentation about 'hdftsa' is provided via the paper by Cristian F. Jimenez-Varon, Ying Sun and Han Lin Shang (2024, <doi:10.1080/10618600.2024.2319166>).
Maintained by Han Lin Shang. Last updated 2 months ago.
1.00 scorecran
srp:Smooth-Rough Partitioning of the Regression Coefficients
Performs the change-point detection in regression coefficients of linear model by partitioning the regression coefficients into two classes of smoothness. The change-point and the regression coefficients are jointly estimated.
Maintained by Hyeyoung Maeng. Last updated 6 years ago.
1.00 score
cvandergeugten
TimeVarConcurrentModel:Concurrent Multivariate Models with Time-Varying Coefficients
Provides a hypothesis test and variable selection algorithm for use in time-varying, concurrent regression models. The hypothesis test function is also accompanied by a plotting function which will show the estimated beta(s) and confidence band(s) from the hypothesis test. The hypothesis test function helps the user identify significant covariates within the scope of a time-varying concurrent model. The plots will show the amount of area that falls outside the confidence band(s) which is used for the test statistic within the hypothesis test.
Maintained by Chance Vandergeugten. Last updated 3 years ago.
1.00 score
popescuc71
TFunHDDC:Clustering of Functional Data via Mixtures of t-Distributions
Extension of 'funHDDC' Schmutz et al. (2018) <doi:10.1007/s00180-020-00958-4> for cases including outliers by fitting t-distributions for robust groups. 'TFunHDDC' can cluster univariate or multivariate data produced by the 'fda' package for data using a b-splines or Fourier basis.
Maintained by Cristina Anton. Last updated 2 years ago.
1.00 score 2 scripts
tianxili
HCD:Hierarchical Community Detection by Recursive Partitioning
Hierarchical community detection on networks by a recursive spectral partitioning strategy, which is shown to be effective and efficient in Li, Lei, Bhattacharyya, Sarkar, Bickel, and Levina (2018) <arXiv:1810.01509>. The package also includes a data generating function for a binary tree stochastic block model, a special case of stochastic block model that admits hierarchy between communities.
Maintained by Tianxi Li. Last updated 1 years ago.
1.00 score 7 scriptscran
FunctanSNP:Functional Analysis (with Interactions) for Dense SNP Data
An implementation of revised functional regression models for multiple genetic variation data, such as single nucleotide polymorphism (SNP) data, which provides revised functional linear regression models, partially functional interaction regression analysis with penalty-based techniques and corresponding drawing functions, etc.(Ruzong Fan, Yifan Wang, James L. Mills, Alexander F. Wilson, Joan E. Bailey-Wilson, and Momiao Xiong (2013) <doi:10.1002/gepi.21757>).
Maintained by Rui Ren. Last updated 2 years ago.
1.00 score
biplab44
ctmva:Continuous-Time Multivariate Analysis
Implements a basis function or functional data analysis framework for several techniques of multivariate analysis in continuous-time setting. Specifically, we introduced continuous-time analogues of several classical techniques of multivariate analysis, such as principal component analysis, canonical correlation analysis, Fisher linear discriminant analysis, K-means clustering, and so on. Details are in Biplab Paul, Philip T. Reiss and Erjia Cui (2023) "Continuous-time multivariate analysis" <doi:10.48550/arXiv.2307.09404>.
Maintained by Biplab Paul. Last updated 1 years ago.
1.00 scorecran
KFPLS:Kernel Functional Partial Least Squares
Implementation for kernel functional partial least squares (KFPLS) method. KFPLS method is developed for functional nonlinear models, and the method does not require strict constraints for the nonlinear structures. The crucial function of this package is KFPLS().
Maintained by Rou Zhong. Last updated 2 years ago.
1.00 score
mirrelijn
ecpc:Flexible Co-Data Learning for High-Dimensional Prediction
Fit linear, logistic and Cox survival regression models penalised with adaptive multi-group ridge penalties. The multi-group penalties correspond to groups of covariates defined by (multiple) co-data sources. Group hyperparameters are estimated with an empirical Bayes method of moments, penalised with an extra level of hyper shrinkage. Various types of hyper shrinkage may be used for various co-data. Co-data may be continuous or categorical. The method accommodates inclusion of unpenalised covariates, posterior selection of covariates and multiple data types. The model fit is used to predict for new samples. The name 'ecpc' stands for Empirical Bayes, Co-data learnt, Prediction and Covariate selection. See Van Nee et al. (2020) <arXiv:2005.04010>.
Maintained by Mirrelijn M. van Nee. Last updated 2 years ago.
1.00 score 9 scriptscran
LocKer:Locally Sparse Estimator of Generalized Varying Coefficient Model for Asynchronous Longitudinal Data
Locally sparse estimator of generalized varying coefficient model for asynchronous longitudinal data by kernel-weighted estimating equation.
Maintained by Rou Zhong. Last updated 3 years ago.
1.00 score
buybnb
CMMs:Compositional Mediation Model
A compositional mediation model for continuous outcome and binary outcomes to deal with mediators that are compositional data. Lin, Ziqiang et al. (2022) <doi:10.1016/j.jad.2021.12.019>.
Maintained by Ziqiang Lin. Last updated 2 years ago.
1.00 score