کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1137481 1489172 2010 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Time series AR modeling with missing observations based on the polynomial transformation
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
Time series AR modeling with missing observations based on the polynomial transformation
چکیده انگلیسی

This paper focuses on parameter estimation problems of auto-regression (AR) time series models with missing observations. The standard estimation algorithms cannot be applied to such AR models with missing observations. The polynomial transformation technique is employed to transform the AR models into models which can be identified from available scarce observations, then the extended stochastic gradient algorithm is proposed to fit the time series with missing observations. The convergence properties of the proposed algorithm are analyzed and an example is given to test and illustrate the conclusions in the paper.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical and Computer Modelling - Volume 51, Issues 5–6, March 2010, Pages 527–536
نویسندگان
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