Browse Items (8208 total)

The Extremes.jl package provides exhaustive, high-performance functions by leveraging the multiple-dispatch capabilities in Julia for the analysis of extreme values. In
particular, the package implements statistical models for both block maxima and…

This article introduces funGp, an R package which handles regression problems involving multiple scalar and/or functional inputs, and a scalar output, through the Gaussian
process model. This is particularly of interest for the design and analysis…

This article presents the magi software package for the inference of dynamic systems.
The focus of magi is on dynamics modeled by nonlinear ordinary differential equations
with unknown parameters. While such models are widely used in science and…

One of the most popular techniques for visualizing large, high-dimensional data sets
is t-distributed stochastic neighbor embedding (t-SNE). Recently, several extensions have
been proposed to address scalability issues and the quality of the…

he library scikit-fda is a Python package for functional data analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. The library is built upon and integrated in…

Two common issues arise in regression modelling of bivariate count data: (i) dependence across outcomes, and (ii) excess zero counts (i.e., zero inflation). However, there
are currently few options to estimate bivariate zero-inflated count…

The library scikit-fda is a Python package for functional data analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. The library is built upon and integrated in…

Two common issues arise in regression modelling of bivariate count data: (i) dependence across outcomes, and (ii) excess zero counts (i.e., zero inflation). However, there
are currently few options to estimate bivariate zero-inflated count…

Non-Gaussian spatial and spatio-temporal data are becoming increasingly prevalent,
and their analysis is needed in a variety of disciplines. FRK is an R package for spatial
and spatio-temporal modeling and prediction with very large data sets that,…

Certain events can make the structure of volatility of financial returns to change,
making it nonstationary. Models of time-varying conditional variance such as generalized
autoregressive conditional heteroscedasticity (GARCH) models usually assume…