کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
418024 681600 2008 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Assessing influence in Gaussian long-memory models
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Assessing influence in Gaussian long-memory models
چکیده انگلیسی

A statistical methodology for detecting influential observations in long-memory models is proposed. The identification of these influential points is carried out by case-deletion techniques. In particular, a Kullback–Leibler divergence is considered to measure the effect of a subset of observations on predictors and smoothers. These techniques are illustrated with an analysis of the River Nile data where the proposed methods are compared to other well-known approaches such as the Cook and the Mahalanobis distances.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 52, Issue 9, 15 May 2008, Pages 4487–4501
نویسندگان
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