Trending Research
Bus Stop Spacings Statistics: Theory and Evidence
Transit agencies have been removing a large number of bus stops, but discussions around the bus stop spacings exhibit a lack of clarity and data for comparison.
Methodology Physics and Society
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
Nested $\hat R$: Assessing Convergence for Markov chain Monte Carlo when using many short chains
google-research/google-research
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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
Probabilistic Programming in Python using PyMC
pymc-devs/pymc3
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Probabilistic programming (PP) allows flexible specification of Bayesian statistical models in code.
Computation
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
Bayesian Time Varying Coefficient Model with Applications to Marketing Mix Modeling
Both Bayesian and varying coefficient models are very useful tools in practice as they can be used to model parameter heterogeneity in a generalizable way.
Applications Methodology
yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties
The yaglm package aims to make the broader ecosystem of modern generalized linear models accessible to data analysts and researchers.
Computation Methodology 62J12, 62J07
Fast Bayesian inference in large Gaussian graphical models
Specifically, we introduce closed-form Bayes factors under the Gaussian conjugate model to evaluate the null hypotheses of marginal and conditional independence between variables.
Methodology
StateSpaceModels.jl: a Julia Package for Time-Series Analysis in a State-Space Framework
StateSpaceModels. jl is an open-source Julia package for modeling, forecasting and simulating time series in a state-space framework.
Computation Optimization and Control
A flexible forecasting model for production systems
This paper discusses desirable properties of forecasting models in production systems.
Methodology
