Designed for optimal use in performing fast, accurate walking strides segmentation from high-density data collected from a wearable accelerometer worn during continuous walking activity.
The BACCO bundle of packages is replaced by the BACCO package, which provides a vignette that illustrates the constituent packages (emulator, approximator, calibrator) in use.
Canonical correlation analysis and maximum correlation via projection pursuit, as well as fast implementations of correlation estimators, with a focus on robust and nonparametric methods.
S4 classes around infrastructure provided by the coda and dclone packages to make package development easy as a breeze with data cloning for hierarchical models.
Estimates fractional trophic level from quantitative and qualitative diet data and calculates electivity indices in R. Borstein (2020) <doi:10.1007/s10750-020-04417-5>.
Finds regular and chaotic intervals in the data using the 0-1 test for chaos proposed by Gottwald and Melbourne (2004) <DOI:10.1137/080718851>.
This package provides a lightweight implementation of functions and methods for fast and fully automatic time series modeling and forecasting using Echo State Networks (ESNs).
Convenience functions for implementing extended two-way fixed effect regressions a la Wooldridge (2021, 2023) <doi:10.2139/ssrn.3906345>, <doi:10.1093/ectj/utad016>.
Interactively applies the Guidelines for Reporting About Network Data (GRAND) to an igraph object, and generates a uniform narrative or tabular description of the object.
The function gggap() streamlines the creation of segments on the y-axis of ggplot2 plots which is otherwise not a trivial task to accomplish.
This package provides tools for using genetic markers, stable isotope data, and habitat suitability data to calculate posterior probabilities of breeding origin of migrating birds.
Enables chat completion and text annotation with local and OpenAI <https://openai.com/> language models, supporting batch processing, multiple annotators, and consistent output formats.
Fast extrapolation of univariate and multivariate time features using K-Nearest Neighbors. The compact set of hyper-parameters is tuned via grid or random search.
k Nearest Neighbors with variable selection, combine grid search and forward selection to achieve variable selection in order to improve k Nearest Neighbors predictive performance.
Computation of various Markovian models for categorical data including homogeneous Markov chains of any order, MTD models, Hidden Markov models, and Double Chain Markov Models.
This package contains logic for computing the statistical association of variable groups, i.e., gene sets, with respect to the principal components of genomic data.
This package provides functionality for Bayesian analysis of replication studies using power prior approaches (Pawel et al., 2023) <doi:10.1007/s11749-023-00888-5>.
An extension of the Fisher Scoring Algorithm to combine PLS regression with GLM estimation in the multivariate context. Covariates can also be grouped in themes.
This package provides the spatial sign correlation and the two-stage spatial sign correlation as well as a one-sample test for the correlation coefficient.
This package implements the Sliding Window Discrete Fourier Transform (SWDFT). Also provides statistical methods based on the SWDFT, and graphical tools to display the outputs.
This package provides tools for visibility analysis in geospatial data. It offers functionality to perform isovist calculations, using arbitrary geometries as both viewpoints and occluders.
An implementation of the variable neighborhood trust region algorithm Bierlaire et al. (2009) "A Heuristic for Nonlinear Global Optimization" <doi:10.1287/ijoc.1090.0343>.
It fits correlation motif model to multiple RNAseq or ChIPseq studies to improve detection of allele-specific events and describe correlation patterns across studies.
SCONE is an R package for comparing and ranking the performance of different normalization schemes for single-cell RNA-seq and other high-throughput analyses.