Since Quetelet's work in the nineteenth century, social science has iconified the average
man, that hypothetical man without qualities who is comfortable with his head in the oven …

This article studies how systemic risk and financial market distress affect the distribution of
shocks to real economic activity. We analyze how changes in 19 different measures of …

Quantile regression is gradually emerging as a unified statistical methodology for estimating
models of conditional quantile functions. By complementing the exclusive focus of classical …

This article focuses on variable selection for partially linear models when the covariates are
measured with additive errors. We propose two classes of variable selection procedures …

In this article, we propose two important measures, quantile correlation (QCOR) and quantile
partial correlation (QPCOR). We then apply them to quantile autoregressive (QAR) models …

Robust statistical methods were developed to supplement the classical procedures when
the data violate classical assumptions. They are ideally suited to applied research across a …

We continue our review of issues related to measurement error and misclassification in
epidemiology. We further describe methods of adjusting for biased estimation caused by …

Untitled Page 1 Page 2 Information Science and Statistics Series Editors: M. Jordan J.
Kleinberg B. Schölkopf Page 3 Information Science and Statistics For other titles published in …

Regression quantiles can be substantially biased when the covariates are measured with
error. In this paper we propose a new method that produces consistent linear quantile …

We study quantile regression estimation for dynamic models with partially varying
coefficients so that the values of some coefficients may be functions of informative …