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10/28/2022
Empirical Macroeconomics and DSGE Modeling in Statistical Perspective
Dynamic stochastic general equilibrium (DSGE) models have been an ubiqui...
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09/19/2022
Exponential Family Trend Filtering on Lattices
Trend filtering is a modern approach to nonparametric regression that is...
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08/05/2022
sparsegl: An R Package for Estimating Sparse Group Lasso
The sparse group lasso is a high-dimensional regression technique that i...
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02/20/2022
Smooth multi-period forecasting with application to prediction of COVID-19 cases
Forecasting methodologies have always attracted a lot of attention and h...
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07/05/2021
Sufficient principal component regression for pattern discovery in transcriptomic data
Methods for global measurement of transcript abundance such as microarra...
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07/14/2019
Markov-switching State Space Models for Uncovering Musical Interpretation
For concertgoers, musical interpretation is the most important factor in...
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07/12/2019
Predicting phenotypes from microarrays using amplified, initially marginal, eigenvector regression
Motivation: The discovery of relationships between gene expression measu...
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05/18/2018
Modeling trend in temperature volatility using generalized LASSO
In this paper, we present methodology for estimating trends in spatio-te...
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02/04/2016
Risk estimation for high-dimensional lasso regression
In high-dimensional estimation, analysts are faced with more parameters ...
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02/02/2016
On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets
In this paper we analyze approximate methods for undertaking a principal...
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08/04/2013
Risk-consistency of cross-validation with lasso-type procedures
The lasso and related sparsity inducing algorithms have been the target ...
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12/03/2012
Nonparametric risk bounds for time-series forecasting
We derive generalization error bounds for traditional time-series foreca...
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11/15/2011
Estimated VC dimension for risk bounds
Vapnik-Chervonenkis (VC) dimension is a fundamental measure of the gener...
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07/21/2011
Spectral approximations in machine learning
In many areas of machine learning, it becomes necessary to find the eige...
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06/03/2011
Rademacher complexity of stationary sequences
We show how to control the generalization error of time series models wh...
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03/04/2011
Generalization error bounds for stationary autoregressive models
We derive generalization error bounds for stationary univariate autoregr...
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03/04/2011
