Research
Publications
Ken McAlinn
Google Scholar
Read papers, find related work, and follow his research on Google Scholar.
No papers match this search.
Published and accepted
Ensemble Doubly Robust Bayesian Inference via Regression Synthesis
A Comment on "Adaptive Treatment Assignment in Experiments for Policy Choice" (2021)
Sequential Dynamic Bayesian Modeling for Single-Case Experimental Designs: A Novel Approach to Many Labs Research
Learning Causal Models from Conditional Moment Restrictions by Importance Weighting
The Adaptive Doubly Robust Estimator and a Paradox Concerning Logging Policy
Mixed-Frequency Bayesian Predictive Synthesis for Economic Nowcasting
Dynamic Variable Selection with Spike-and-Slab Process Priors
Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting
Volatility Forecasts Using Stochastic Volatility Models with Nonlinear Leverage Effects
Dynamic Bayesian predictive synthesis in time series forecasting
Discussion of “Using Stacking to Average Bayesian Predictive Distributions,” by Yao et al.
Stochastic volatility models and its application to VIX derivatives (in Japanese)
Working papers
An Entropy–Energy Identity for Predictive Kullback–Leibler Regret in Infinitely Divisible Location Models
Potential Outcomes on Stochastic Processes: A Framework for Causal Inference in Time Series Interventions
Fast Boundary-Aware Spatial Intensity Estimation on Complex Domains
FlowSDR: Sufficient Dimension Reduction via Conditional Normalizing Flows
Utility-Based Design of Hold-Out Validation
Predictive Synthesis under Sporadic Participation: Evidence from Inflation Density Surveys
When Is Generalized Bayes Bayesian?
Bootstrap-Based False Discovery Control under Dependence: An Application to Asset Pricing Anomalies
Bayesian Causal Synthesis for Meta-Inference on Heterogeneous Treatment Effects
Patent Waiver and Incentives to Innovate
Ensembling under Statistical Pluralism: A Taxonomy of Formulations, Diagnostics, and Reporting
When Linear Forecast Combinations Fail: The Geometry of Ensembling
Multivariate Dynamic Treatment Effects: A Model-Based Causal Estimator, Decomposition, and Marketing Applications
Dirichlet Geometry for Posterior Sensitivity
Dynamic Interrupted Time Series Analysis
Testing Density Continuity Along Irregular Treatment Boundaries
From Trial Averages to Target Effects: Bayesian CATE Synthesis with Randomized and Observational Evidence
Path-Space Shrinkage for Predictive Density Estimation
Model Averaging and Vincentization Are Not Minimax
Numerical Approximation of Dynamic Models with Multiple Invariant Measures
Improving Implicit Under-Parameterization in Ensemble Learning via Mean-Shift
How Fast Do Markets Learn? Dynamic Post-Publication Decay of Asset-Pricing Anomalies
Probability as a Normative Role
Inadmissibility and Transience
Equivariant online predictions of non-stationary time series
Previously circulated as Predictive properties of forecast combination, ensemble methods, and Bayesian predictive synthesis.
Controlling False Discovery Rates under Cross-Sectional Correlations
Convergence of Computed Dynamic Models with Unbounded Shock
Divide and Conquer: Financial Ratios and Industry Returns Predictability
Previously circulated as Large-Scale Dynamic Predictive Regressions.
Mean-shift least squares model averaging
Dynamic Sparse Factor Analysis
Fully Parallel Particle Learning for GPGPUs and Other Parallel Devices