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Influence Measure (influence + measure)

Distribution by Scientific Domains
Mathematics and Statistics66%

Selected Abstracts

A new approach to influence diagnostics in superpopulations

ENVIRONMETRICS, Issue 4 2005
J. M. Fernández-Ponce
Abstract Influence analysis on a model is one of the most studied topics from a frequentist viewpoint. Basically, disturbances are introduced into the model in order to measure the influence that one or a set of observations has on statistical analysis. The most common disturbance pattern is that of the omission of the observations whose influence is to be studied. In our model, we assume that there are only one or a few outliers because they may often be detected by deletion methods associated with regression diagnostics. However, these methods may fail in the presence of multiple outliers. In this case, the forward search can be used to avoid the masking and swamping problems. This article presents a Bayes approach for the influence analysis on a model in finite populations. Particularly, we develop a new approach to the study of influence in prediction theory, based on the given data rather than on the sampling design for data collection. We propose that the influence analysis on the superpopulation normal regression model and a measure based on the conditional bias from a Bayesian viewpoint is analyzed. Forward deletion formulae based on our influence measure can be defined, but this topic is beyond the scope of this article. Finally, we apply our proposed influence measure in a classic example for water contents of soil specimens. Copyright © 2005 John Wiley & Sons, Ltd. [source]

A prototype store choice and location modelling system using Dempster,Shafer theory

EXPERT SYSTEMS, Issue 5 2002
Malcolm Beynon
This paper concerns the study of destination choice modelling, more specifically identifying within some area (e.g. a city) the region where a particular store is the most favourable to be visited by individuals. An influence measure is constructed for each individual, which incorporates the modern technique known as Dempster,Shafer theory. Based on the evidence of the shopping destinations of individuals, geographical regions are found for levels of largest belief and plausibility (within Dempster,Shafer theory) for specific stores being the most favourable to visit. Additionally, this method may be used to identify the possible position of new stores, based on regions of most uncertainty or conflict in store choice. A prototype choice modelling system is introduced to enable the series of associated results to be easily visualized and analysed. [source]

DETECTING INFLUENTIAL OBSERVATIONS IN SLICED INVERSE REGRESSION ANALYSIS

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 3 2006
Luke A. Prendergast
Summary The detection of influential observations on the estimation of the dimension reduction subspace returned by Sliced Inverse Regression (SIR) is considered. Although there are many measures to detect influential observations in related methods such as multiple linear regression, there has been little development in this area with respect to dimension reduction. One particular influence measure for a version of SIR is examined and it is shown, via simulation and example, how this may be used to detect influential observations in practice. [source]

Influence diagnostics and outlier tests for semiparametric mixed models

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 3 2002
Wing-Kam Fung
Summary. Semiparametric mixed models are useful in biometric and econometric applications, especially for longitudinal data. Maximum penalized likelihood estimators (MPLEs) have been shown to work well by Zhang and co-workers for both linear coefficients and nonparametric functions. This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric component. We focus on influence measures for the fixed effects and provide formulae that are analogous to those for simpler models and readily computable with the MPLE algorithm. We also establish an equivalence between the case or subject deletion model and a mean shift outlier model from which we derive tests for outliers. The influence diagnostics proposed are illustrated through a longitudinal hormone study on progesterone and a simulated example. [source]

Evidence for a female-specific effect of a chromosome 4 locus on anxiety-related behaviors and ethanol drinking in rats

GENES, BRAIN AND BEHAVIOR, Issue 6 2006
L. F. Vendruscolo
Previous studies using the inbred rat strains Lewis (LEW) and spontaneously hypertensive rats (SHR) led to the mapping of two quantitative trait loci, named Ofil1 (on chromosome 4 of the rat) and Ofil2 (on chromosome 7), for open-field inner locomotion, a behavioral index of anxiety. Studies using other strains showed that the region next to Ofil1 influences measures of not only anxiety but also ethanol consumption. In view of the high prevalence of psychiatric disorders such as anxiety and alcoholism, as well as the comorbidity between them, the present study was designed to better characterize the contribution of these two loci to complex emotional and consummatory responses. Rats deriving from an F2 intercross between the LEW and the SHR strains were selected according to their genotype at markers flanking the loci Ofil1 and Ofil2 and bred to obtain lines of rats homozygous LEW/LEW or SHR/SHR for each of the two loci, thus generating four genotypic combinations. These selected animals as well as purebred LEW and SHR rats of both sexes were submitted to a battery of tests including measures of locomotor activity, anxiety, sweet and bitter taste reinforcement and ethanol intake. Lewis rats displayed more anxiety-like behavior and less ethanol intake than SHR rats. Ofil1 (on chromosome 4) affected both the activity in the center of the open field and ethanol drinking in females only. These results suggest that Ofil1 contains either linked genes with independent influences on anxiety-related responses and ethanol drinking or a pleiotropic gene with simultaneous effects on both traits. [source]