## 372 Citations

Asymptotically Efficient Model Selection for Panel Data Forecasting

- Economics, Mathematics
- 2018

This paper develops new model selection methods for forecasting panel data using a set of least squares (LS) vector autoregressions. Model selection is based on minimizing the estimated quadratic…

Two essays in statistics: a prediction divergence criterion for model selection & wavelet variance based estimation of latent time series models

- Computer Science, Mathematics
- 2013

A new criterion for model selection is presented which is shown to be particularly well suited in "sparse" settings which is believed to be common in many research fields and an alternative to maximum likelihood estimation is presented.

Uniform moment bounds of Fisher's information with applications to time series

- Mathematics, Computer Science
- 2012

An asymptotic expression for the mean squared prediction error of the least squares predictor in autoregressive moving average models is obtained and provides a solid theoretical foundation for some model selection criteria.

Network ensemble and constructive algorithms for model selection of extreme learning machine

- Computer Science
- 2011

The Focussed Information Criterion

- Mathematics, Computer Science
- 2011

A focussed information criterion for model selection, the FIC, is proposed using an unbiased estimate of limiting risk, and a method which for given focus parameter estimates the precision of any submodel-based estimator is developed.

Issues in Model Selection, Minimax Estimation, and Censored Data Analysis

- Mathematics
- 2007

In this dissertation, we address several research problems in statistical inference. We obtain results in the following four directions: linear model selection, minimax estimation of linear…

DIRECT AUTOREGRESSIVE PREDICTORS FOR MULTISTEP PREDICTION: ORDER SELECTION AND PERFORMANCE RELATIVE TO THE PLUG IN PREDICTORS

- Mathematics
- 1997

A direct method for multistep prediction of a stationary time series con- sists of fitting a new autoregression for each lead time, h, by a linear regression procedure and to select the order to be…

SELECTION OF A MULTISTEP LINEAR PREDICTOR FOR SHORT TIME SERIES

- Mathematics
- 1997

We develop a version of the Corrected Akaike Information Criterion (AICC) suitable for selection of an h-step-ahead linear predictor for a weakly sta- tionary time series in discrete time. A…

Selecting neural network architectures via the prediction risk: application to corporate bond rating prediction

- Computer ScienceProceedings First International Conference on Artificial Intelligence Applications on Wall Street
- 1991

The authors propose the prediction risk as a measure of the generalization ability of multi-layer perceptron networks and use it to select the optimal network architecture.