In survey sampling, ratio and regression estimators are often used to estimate the mean of a finite population. These estimators make use of information on an auxiliary variable that is assumed to be available over the entire population. Generally speaking, the higher the correlation between the response and this auxiliary variable, the more efficient the ratio and regression estimators will be...

This study proposes a new use of goal programming for empirically estimating a regression quantile hyperplane. The approach can yield regression quantile estimates that are less sensitive to not only non-Gaussian error distribut.ions but also a small sample size t.han conventional regression quantile methods. The performance of regression quantile estimates is compared with least absolute value...

This paper describes a fast and efficient technique to calculate approximate LAV (Least Absolute Value) solutions in power system state estimation. The method uses a two level approach in which accurate LAV solutions are obtained on a slower time scale and approximate LAV solutions are obtained by solving generalized power flows on a much faster time scale. These approximate LAV estimates, whic...

Logical analysis of data (LAD) is one of the methodologies for extracting knowledge as a Boolean function f from a given pair of data sets (T; F ) on attributes set S of size n, in which T (resp., F ) f0; 1g n denotes a set of positive (resp., negative) examples for the phenomenon under consideration. In this paper, we consider the case in which extracted knowledge has a decomposable structure;...

Genetic assimilation is a possible neo-Darwininan mechanism for the emer-gence and subsequent refinement of the putative innate human language acqui-sition device (LAD). The LAD, in the weak sense of language-specific inductivebias, is a part of all extant models of grammatical acquisition. A survey of argu-ments and counterarguments for the assimilation of such bias during ...

The convexity arguments developed by Pollard [D. Pollard, Asymptotics for least absolute deviation regression estimators, Econometric Theory 7 (1991) 186–199], Hjort and Pollard [N.L. Hjort, D. Pollard, Asymptotics for minimizers of convex processes, 1993 (unpublished manuscript)], and Geyer [C.J. Geyer, On the asymptotics of convex stochastic optimization, 1996 (unpublished manuscript)] are no...

In this paper, the high-dimensional sparse linear regression model is considered, where the overall number of variables is larger than the number of observations. We investigate the L1 penalized least absolute deviation method. Different from most of other methods, the L1 penalized LAD method does not need any knowledge of standard deviation of the noises or any moment assumptions of the noises...

For regression, y is real valued, L is the often squared loss (but not always; for example see Least Absolute Deviation regression) and w is the best linear fit to the data. For binary classification, y is binary, L is often the 0/1 loss and w is the best hyperplane separating the two sets of samples. Since the 0/1 loss is nonconvex, we often use convex upper bounds for the 0/1 loss examples of...

The Leadership Academy for Development (LAD) trains government officials and business leaders from developing countries to help the private sector be a constructive force for economic growth and development. It teaches carefully selected participants how to be effective reform leaders, promoting sound public policies in complex and contentious settings. AD Chris Walker prepared this case under ...