Seminars in Statistics
Seminars in Statistics
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Seminars in Statistics Natesh Pillai (Harvard University)
Seminars in Statistics Natesh Pillai (Harvard University)
Bayesian Factor Models in High Dimensions Sparse Bayesian factor models are routinely implemented for parsimonious dependence modeling and dimensionality reduction in high-dimensional applications. We provide theoretical understanding of such Bayesian procedures in terms of posterior convergence rates in inferring high-dimensional covariance matrices where the dimension can be larger than the sample size. We will also…
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Seminars in Statistics Steven Scott (Google)
Seminars in Statistics Steven Scott (Google)
Predicting the Present with Bayesian Structural Time Series This article describes a system for short term forecasting based on an ensemble prediction that averages over different combinations of predictors. The system combines a structural time series model for the target series with regression component capturing the contributions of contemporaneous search query data. A spike-and-slab prior…