On eigenvalues, case deletion and extremes in regression

This paper presents an approximation for assessing the effect of deleting an observation in the eigenvalues of the correlation matrix of a multiple linear regression modelo Applications in connection with the detection of collinearityinfluential observations are explored

On the behaviour of residual plots in regression

Properties of least squares versus robust regression residual plots are compared under a common set of assumptions

A quantile approach to the box-cox transformation in random samples.

This paper presents an alternative approach to the likelihood methods for estimating the parameter A in the Box-Cox family of transformations when the data arise from a random sample. The method is based on a representation of the quantile function of the variable under consideration. Theoretical properties of the method, its practical applications and comparison with the likelihood approach are studied.Asymptotic relative efficiency (ARE); Box-Cox transformation; Influential observations; Quantile function; Kernel density estimation;

ON THE CONSISTENCY AND ROBUSTNESS PROPERTIES OF LINEAR DISCRIMINANT ANALYSIS

Strong consistency of linear discriminant analysis is established under wide assumptions on the class conditional densities. Robustness to the presence of a mild degree of class dispersion heterogeneity is also analyzed. Results obtained may help to explain analytically the frequent good behavior in applications of linear discrimination techniques.

Hedonic house prices without characteristics: the case of new multiunit housing

In this paper we propose an alternative to traditional hedonics for estimating new multiunit housing inflation, adjusting for quality changes. By relying on the within-site variation we control in a very general way for unobserved housing characteristics using site-specific effects. Precise location, transport, traffic, closeness to services, or construction quality are some of the unobserved but typically relevant housing characteristics that may bias estimated house price inflation, even when using hedonic methods. We also estimate standard hedonic equations and compare the results to those obtained with the alternative hedonic equations with site dummies. Our dataset is fairly rich in observable housing characteristics but, nevertheless, the quality-adjusted house price evolution is quite different in some cases. The data cover the construction of new housing in some of the large Spanish cities and in the smaller towns on the outskirts of the capital during part of the 1990s. JEL Classification: C43, E31, O47, R31

A quantile approach to the box-cox transformation in random samples

This paper presents an alternative approach to the likelihood methods for estimating the parameter A in the Box-Cox family of transformations when the data arise from a random sample. The method is based on a representation of the quantile function of the variable under consideration. Theoretical properties of the method, its practical applications and comparison with the likelihood approach are studied

Diagnostics and robust estimation in multivariate data transformations

This paper presents a method for detecting multivariate outliers which might be distorting theı estimation of a transformation to normality. A robust estimator of the transformation parameter is also proposed

A note on the multivariate box-cox transformation to normality

We study some aspects of the multivariate Box-Cox transformation to normality which have received little attention in the literature

On eigenvalues, case deletion and extremes in regression.

This paper presents an approximation for assessing the effect of deleting an observation in the eigenvalues of the correlation matrix of a multiple linear regression modelo Applications in connection with the detection of collinearityinfluential observations are explored.Case deletion; Collinearity; Eigenvalues; Extreme cases; Gateaux differentiability; Multiple Linear Regression; Perturbation theory;