کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7408422 | 1481440 | 2015 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems
ترجمه فارسی عنوان
محدودیت های مدل بینایی بیزی به طور میانگین برای پیش بینی مشکلات اجتماعی
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کلمات کلیدی
تجزیه و تحلیل بیزی، ترکیب پیش بینی ها، پیش بینی اقتصادی، پیش بینی انتخابات، وزنه های برابر،
موضوعات مرتبط
علوم انسانی و اجتماعی
مدیریت، کسب و کار و حسابداری
کسب و کار و مدیریت بین المللی
چکیده انگلیسی
We compare the accuracies of simple unweighted averages and Ensemble Bayesian Model Averaging (EBMA) for combining forecasts in the social sciences. A review of prior studies from the domain of economic forecasting finds that the simple average was more accurate than EBMA in four studies out of five. On average, the error of EBMA was 5% higher than that of the simple average. A reanalysis and extension of a published study provides further evidence for US presidential election forecasting. The error of EBMA was 33% higher than the corresponding error of the simple average. Simple averages are easy both to describe and to understand, and thus are easy to use. In addition, simple averages provide accurate forecasts in many settings. Researchers who are developing new approaches to combining forecasts need to compare the accuracy of their method to this widely established benchmark. Forecasting practitioners should favor simple averages over more complex methods unless there is strong evidence in support of differential weights.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Forecasting - Volume 31, Issue 3, JulyâSeptember 2015, Pages 943-951
Journal: International Journal of Forecasting - Volume 31, Issue 3, JulyâSeptember 2015, Pages 943-951
نویسندگان
Andreas Graefe, Helmut Küchenhoff, Veronika Stierle, Bernhard Riedl,