Time series forecasting is an active research topic in academia as well as industry.
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.
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.
This paper discusses desirable properties of forecasting models in production systems.
State-space models (SSM) with Markov switching offer a powerful framework for detecting multiple regimes in time series, analyzing mutual dependence and dynamics within regimes, and asserting transitions between regimes.
Quantile regression is a statistical method for estimating conditional quantiles of a response variable.
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