Trending Research
Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models
When fitting black box supervised learning models (e. g., complex trees, neural networks, boosted trees, random forests, nearest neighbors, local kernel-weighted methods, etc.
Methodology
ergm 4: Computational Improvements
The ergm package supports the statistical analysis and simulation of network data.
Computation
A User-Focused Approach to Evaluating Probabilistic and Categorical Forecasts
A user-focused verification approach for evaluating probability forecasts of binary outcomes (also known as probabilistic classifiers) is demonstrated that is (i) based on proper scoring rules, (ii) focuses on user decision thresholds, and (iii) provides actionable insights.
Applications
A large-scale analysis of racial disparities in police stops across the United States
We find that black drivers are stopped more often than white drivers relative to their share of the driving-age population, but that Hispanic drivers are stopped less often than whites.
Applications
ruptures: change point detection in Python
ruptures is a Python library for offline change point detection.
Computation Mathematical Software
Multilevel Delayed Acceptance MCMC
pymc-devs/pymc
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We develop a novel Markov chain Monte Carlo (MCMC) method that exploits a hierarchy of models of increasing complexity to efficiently generate samples from an unnormalized target distribution.
Methodology Computation 62F15, 62M05, 65C05, 65C40
Fitting Matérn Smoothness Parameters Using Automatic Differentiation
The Mat\'ern covariance function is ubiquitous in the application of Gaussian processes to spatial statistics and beyond.
Computation Methodology
vivid: An R package for Variable Importance and Variable Interactions Displays for Machine Learning Models
We present vivid, an R package for visualizing variable importance and variable interactions in machine learning models.
Computation
Machine learning assisted Bayesian model comparison: learnt harmonic mean estimator
astro-informatics/harmonic
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It was immediately realised that the original estimator can fail catastrophically since its variance can become very large (possibly not finite).
Methodology Instrumentation and Methods for Astrophysics Computation
Integrated Emulators for Systems of Computer Models
We generalize the state-of-the-art linked emulator for a system of two computer models under the squared exponential kernel to an integrated emulator for any feed-forward system of multiple computer models, under a variety of kernels (exponential, squared exponential, and two key Mat\'ern kernels) that are essential in advanced applications.
Methodology Applications
