کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5077200 | 1374121 | 2009 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A parameterized approach to modeling and forecasting mortality
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A new method is proposed of constructing mortality forecasts. This parameterized approach utilizes Generalized Linear Models (GLMs), based on heteroscedastic Poisson (non-additive) error structures, and using an orthonormal polynomial design matrix. Principal Component (PC) analysis is then applied to the cross-sectional fitted parameters. The produced model can be viewed either as a one-factor parameterized model where the time series are the fitted parameters, or as a principal component model, namely a log-bilinear hierarchical statistical association model of Goodman [Goodman, L.A., 1991. Measures, models, and graphical displays in the analysis of cross-classified data. J. Amer. Statist. Assoc. 86(416), 1085-1111] or equivalently as a generalized Lee-Carter model with p interaction terms. Mortality forecasts are obtained by applying dynamic linear regression models to the PCs. Two applications are presented: Sweden (1751-2006) and Greece (1957-2006).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Insurance: Mathematics and Economics - Volume 44, Issue 1, February 2009, Pages 103-123
Journal: Insurance: Mathematics and Economics - Volume 44, Issue 1, February 2009, Pages 103-123
نویسندگان
P. Hatzopoulos, S. Haberman,