Furthermore we use $\mathfrak n \hat R$ to construct a warmup scheme with an adaptive length, allowing users to avoid running their MCMC algorithms longer than necessary.
Methodology
This paper discusses desirable properties of forecasting models in production systems.
Methodology
ruptures is a Python library for offline change point detection.
Computation Mathematical Software
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
We present on-line algorithms for computing approximations of rank-based statistics that give high accuracy, particularly near the tails of a distribution, with very small sketches.
Sequential Quantile Estimation
Computation
Data Structures and Algorithms
Probabilistic programming (PP) allows flexible specification of Bayesian statistical models in code.
Computation
Applying BLiP to existing state-of-the-art analyses of UK Biobank data (for genetic fine-mapping) and the Sloan Digital Sky Survey (for astronomical point source detection) increased resolution-adjusted power by 30-120% in just a few minutes of computation.
Methodology 62F15 (Primary), 60G35, 62F25, 62F15, 62J12, 85A35, 92D10 (Secondary)
Analogous to bias correction for inexact matching, Augmented SCM uses an outcome model to estimate the bias due to imperfect pre-treatment fit and then de-biases the original SCM estimate.
Methodology Econometrics
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
Time series forecasting is an active research topic in academia as well as industry.
Computation Methodology