activity
20152021
most citedProgramming with models: writing statistical algorithms for general model structures with NIMBLE

1.1k citations · 1.1k across the 9 of their papers we have counts for

collaborators

9 papers

math.PR2021

When Rooks Miss: Probability through Chess

Steven J. Miller, Haoyu Sheng, Daniel Turek

A famous (and hard) chess problem asks what is the maximum number of safe squares possible in placing queens on an board. We examine related problems from placing $…

stat.AP2020★ 14 cited

Bayesian Non-Parametric Detection Heterogeneity in Ecological Models

Daniel Turek, Claudia Wehrhahn, Olivier Gimenez

Detection heterogeneity is inherent to ecological data, arising from factors such as varied terrain or weather conditions, inconsistent sampling effort, or heterogeneity of individ…

stat.CO2019

Bayesian inference for high-dimensional nonstationary Gaussian processes

Mark D. Risser, Daniel Turek

In spite of the diverse literature on nonstationary spatial modeling and approximate Gaussian process (GP) methods, there are no general approaches for conducting fully Bayesian in…

stat.AP2018★ 68 cited

Diversity of Artists in Major U.S. Museums

Chad M. Topaz, Bernhard Klingenberg, Daniel Turek +6

The U.S. art museum sector is grappling with diversity. While previous work has investigated the demographic diversity of museum staffs and visitors, the diversity of artists in th…

stat.ME2018

Automatic adaptation of MCMC algorithms

Dao Nguyen, Perry de Valpine, Yves Atchade +3

Markov chain Monte Carlo (MCMC) methods are ubiquitous tools for simulation-based inference in many fields but designing and identifying good MCMC samplers is still an open questio…

stat.CO2017★ 3 cited

Sequential Monte Carlo Methods in the nimble R Package

Nicholas Michaud, Perry de Valpine, Daniel Turek +2

nimble is an R package for constructing algorithms and conducting inference on hierarchical models. The nimble package provides a unique combination of flexible model specification…