کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7496047 | 1485763 | 2015 | 30 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparing INLA and OpenBUGS for hierarchical Poisson modeling in disease mapping
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کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت
پزشکی و دندانپزشکی
سیاست های بهداشت و سلامت عمومی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Comparing INLA and OpenBUGS for hierarchical Poisson modeling in disease mapping Comparing INLA and OpenBUGS for hierarchical Poisson modeling in disease mapping](/preview/png/7496047.png)
چکیده انگلیسی
The recently developed R package INLA (Integrated Nested Laplace Approximation) is becoming a more widely used package for Bayesian inference. The INLA software has been promoted as a fast alternative to MCMC for disease mapping applications. Here, we compare the INLA package to the MCMC approach by way of the BRugs package in R, which calls OpenBUGS. We focus on the Poisson data model commonly used for disease mapping. Ultimately, INLA is a computationally efficient way of implementing Bayesian methods and returns nearly identical estimates for fixed parameters in comparison to OpenBUGS, but falls short in recovering the true estimates for the random effects, their precisions, and model goodness of fit measures under the default settings. We assumed default settings for ground truth parameters, and through altering these default settings in our simulation study, we were able to recover estimates comparable to those produced in OpenBUGS under the same assumptions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Spatial and Spatio-temporal Epidemiology - Volumes 14â15, JulyâOctober 2015, Pages 45-54
Journal: Spatial and Spatio-temporal Epidemiology - Volumes 14â15, JulyâOctober 2015, Pages 45-54
نویسندگان
R. Carroll, A.B. Lawson, C. Faes, R.S. Kirby, M. Aregay, K. Watjou,