کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1149098 957862 2010 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Maximum likelihood estimation for directional conditionally autoregressive models
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
Maximum likelihood estimation for directional conditionally autoregressive models
چکیده انگلیسی

A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed using only the inter-distances or boundaries between the regions. To accommodate directional spatial variation, a new class of spatial models is proposed using different weights given to neighbors in different directions. The proposed model generalizes the usual CAR model by accounting for spatial anisotropy. Maximum likelihood estimators are derived and shown to be consistent under some regularity conditions. Simulation studies are presented to evaluate the finite sample performance of the new model as compared to the CAR model. Finally, the method is illustrated using a data set on the crime rates of Columbus, OH and on the elevated blood lead levels of children under the age of 72 months observed in Virginia in the year of 2000.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 140, Issue 11, November 2010, Pages 3160–3179
نویسندگان
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