Titlebook: Nonlinear Time Series; Nonparametric and Pa Jianqing Fan,Qiwei Yao Book 2003 Springer-Verlag New York 2003 Time series.econometrics.linear

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書目名稱Nonlinear Time Series影響因子(影響力)




書目名稱Nonlinear Time Series影響因子(影響力)學(xué)科排名




書目名稱Nonlinear Time Series網(wǎng)絡(luò)公開度




書目名稱Nonlinear Time Series網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Nonlinear Time Series被引頻次




書目名稱Nonlinear Time Series被引頻次學(xué)科排名




書目名稱Nonlinear Time Series年度引用




書目名稱Nonlinear Time Series年度引用學(xué)科排名




書目名稱Nonlinear Time Series讀者反饋




書目名稱Nonlinear Time Series讀者反饋學(xué)科排名

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https://doi.org/10.1007/978-0-387-69395-8Time series; econometrics; linear optimization; mathematical statistics; modeling; nonparametric methods;

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ARMA Modeling and Forecasting,Fitting an appropriate ARMA(.) model to an observed time series data set involves two interrelated problems, namely determining the order (.) (which is usually referred to as model identification) and estimating parameters in the model. Further, the postfitting diagnostic checking on the validity of the fitted model is equally important.

AFFIX

0172-7397 big data warehouses readily accessible. Although cl- sic parametric models, which postulate global structures for underlying systems, are still very useful, la978-0-387-26142-3978-0-387-69395-8Series ISSN 0172-7397 Series E-ISSN 2197-568X

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al from earlier in the book. Some of the results which we will discuss are proved in the literature in the context of Chevalley groups. Refer to the Concluding Remarks of this book for a brief introduction to these groups and some indication as to how they are related to the unitary group of a quadratic module.