Browse Items (12 total)

The stochastic block model is a popular probabilistic model for random graphs. It is
commonly used to cluster network data by aggregating nodes that share similar connectivity patterns into blocks. When fitting a stochastic block model to a…

Bayesian synthetic likelihood (BSL; Price, Drovandi, Lee, and Nott 2018) is a popular
method for estimating the parameter posterior distribution for complex statistical models
and stochastic processes that possess a computationally intractable…

We describe a new algorithm and R package for peak detection in genomic data sets
using constrained changepoint models. These detect changes from background to peak
regions by imposing the constraint that the mean should alternately increase then…

Linear transformation models, including the proportional hazards model and proportional odds model, under right censoring were discussed by Chen, Jin, and Ying (2002).
The asymptotic variance of the estimator they proposed has a closed form and can…

Markov random fields on two-dimensional lattices are behind many image analysis
methodologies. mrf2d provides tools for statistical inference on a class of discrete stationary Markov random field models with pairwise interaction, which includes many…

This paper presents the tidypaleo package for R, which enables high-quality reproducible visualizations of time-stratigraphic multivariate data that is common to several
disciplines of the natural sciences. Rather than introduce new plotting…

Like many groups considering the new programming language Julia, we faced the
challenge of accessing the algorithms that we develop in Julia from R. Therefore, we
developed the R package JuliaConnectoR, available from the Comprehensive R…

Non-regression-based inferences, such as discriminant analysis, can account for the
effect of predictor distributions that may be significant in big data modeling. We describe bbl, an R package for Boltzmann Bayes learning, which enables a…

This paper introduces the usage and performance of the R package tlrmvnmvt, aimed
at computing high-dimensional multivariate normal and Student-t probabilities. The
package implements the tile-low-rank methods with block reordering and the…

This paper introduces the R package FKSUM, which offers fast and exact evaluation of
univariate kernel smoothers. The main kernel computations are implemented in C++, and
are wrapped in simple, intuitive and versatile R functions. The fast kernel…