4 papers
Universal inference with composite likelihoods
Hien D Nguyen, Jessica Bagnall-Guerreiro, Andrew T Jones
Maximum composite likelihood estimation is a useful alternative to maximum likelihood estimation when data arise from data generating processes (DGPs) that do not admit tractable j…
Universal Inference with Composite Likelihoods
Hien Duy Nguyen
Wasserman et al. (2020, PNAS, vol. 117, pp. 16880-16890) constructed estimator agnostic and finite-sample valid confidence sets and hypothesis tests, using split-data likelihood ra…
The fully-visible Boltzmann machine and the Senate of the 45th Australian Parliament in 2016
Jessica J. Bagnall, Andrew T. Jones, Natalie Karavarsamis +1
After the 2016 double dissolution election, the 45th Australian Parliament was formed. At the time of its swearing in, the Senate of the 45th Australian Parliament consisted of nin…
Positive data kernel density estimation via the logKDE package for R
Andrew T. Jones, Hien D. Nguyen, Geoffrey J. McLachlan
Kernel density estimators (KDEs) are ubiquitous tools for nonparametric estimation of probability density functions (PDFs), when data are obtained from unknown data generating proc…