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In this article, a method is proposed to get the limiting distributions and asymptotic properties of estimators based on the minimum and/or maximum of a given srs of a truncated distribution. Following a common outline, a review is carried out by considering different kinds of truncated distributions, some new results are also developed. [ABSTRACT FROM AUTHOR]

In influence analysis several problems arise in the field of Principal Components when applying different sample versions. Among these are the difficulty of determining a certain correspondence between the eigenvalues before and after the deletion of observations, the choice of the sign of the eigenvectors and the computational problem derived from the resolution of a great number of eigenproblems. In this article, such problems are discussed from the joint influence point of view and a solution is proposed by using approximations. Furthermore, the influence on a new parameter of interest is introduced: the proportion of variance explained by a set of principal components. [ABSTRACT FROM AUTHOR]

We propose a diagnostic to assess the influence of a unit ui in the sample s, selected from a finite population U={u1,....,uN} using a sampling design D, on θ^(s) as an estimator of a population parameter θ=θ(Y1,...,YN). We adjust the definition of conditional bias (Muñoz-Picardo et al., 1995), in order to obtain an influence diagnostic in survey sampling. Conditional bias as an influence measure of unit ui (ui∈s) on θ^(s), depends on Yi and on the sampling design, D. This is a distinctive feature of sample surveys. Only in particular cases is the proposed influence measure a case-deletion diagnostic. [ABSTRACT FROM PUBLISHER]

We propose a method for detecting outlier components in two-way contingency tables, using the hypothesis of homogeneity, based on the adjusted residuals. [ABSTRACT FROM PUBLISHER]