Michael Smith

Deep distributional time series models and the probabilistic forecasting of intraday electricity prices

Nadja Klein, Michael Stanley Smith, David J Nott

Journal article  |  2023  |  Journal of Applied Econometrics

Fast and accurate variational inference for models with many latent variables

Ruben Loaiza-Maya, Michael Stanley Smith, David J Nott, Peter J Danaher

Journal article  |  2022  |  JOURNAL OF ECONOMETRICS

Models with a large number of latent variables are often used to utilize the information in big or complex data, but can be diffic..

Interpretable modelling of retail demand and price elasticity for passenger flights using booking data

Jan Felix Meyer, Goeran Kauermann, Michael Stanley Smith

Journal article  |  2022  |  STATISTICAL MODELLING

We propose a model of retail demand for air travel and ticket price elasticity at the daily booking and individual flight level. D..

Implicit Copulas: An Overview

MS Smith

Journal article  |  2022  |  Econometrics and Statistics

Implicit copulas are the most common copula choice for modeling dependence in high dimensions. This broad class of copulas is intr..

Implicit Copula Variational Inference

MS Smith, R Loaiza-Maya

Journal article  |  2022  |  Journal of Computational and Graphical Statistics

Key to effective generic, or “black-box,” variational inference is the selection of an approximation to the target density that ba..

Marginally Calibrated Deep Distributional Regression

Nadja Klein, David J Nott, Michael Stanley Smith

Journal article  |  2021  |  Journal of Computational and Graphical Statistics

Deep neural network (DNN) regression models are widely used in applications requiring state-of-the-art predictive accuracy. Howeve..

Bayesian Inference for Regression Copulas

MS Smith, N Klein

Journal article  |  2021  |  Journal of Business and Economic Statistics

We propose a new semiparametric distributional regression smoother that is based on a copula decomposition of the joint distributi..

Bayesian variable selection for non-Gaussian responses: a marginally calibrated copula approach

Nadja Klein, Michael Stanley Smith

Journal article  |  2020  |  BIOMETRICS

We propose a new highly flexible and tractable Bayesian approach to undertake variable selection in non-Gaussian regression models..

Advertising Effectiveness for Multiple Retailer-Brands in a Multimedia and Multichannel Environment

Peter J Danaher, Tracey S Danaher, Michael Stanley Smith, Ruben Loaiza-Maya

Journal article  |  2020  |  Journal of Marketing Research

An important aspect of multimedia advertising effectiveness that remains unexplored is a customer-level analysis of the relative i..

High-Dimensional Copula Variational Approximation Through Transformation

Michael Stanley Smith, Ruben Loaiza-Maya, David J Nott

Journal article  |  2020  |  Journal of Computational and Graphical Statistics

Variational methods are attractive for computing Bayesian inference when exact inference is impractical. They approximate a target..