Titlebook: Advances in Time Series Methods and Applications; The A. Ian McLeod Fe Wai Keung Li,David A. Stanford,Hao Yu Book 2016 Springer Science+Bus

Enlightening

書目名稱Advances in Time Series Methods and Applications影響因子(影響力)




書目名稱Advances in Time Series Methods and Applications影響因子(影響力)學(xué)科排名




書目名稱Advances in Time Series Methods and Applications網(wǎng)絡(luò)公開度




書目名稱Advances in Time Series Methods and Applications網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Advances in Time Series Methods and Applications被引頻次




書目名稱Advances in Time Series Methods and Applications被引頻次學(xué)科排名




書目名稱Advances in Time Series Methods and Applications年度引用




書目名稱Advances in Time Series Methods and Applications年度引用學(xué)科排名




書目名稱Advances in Time Series Methods and Applications讀者反饋




書目名稱Advances in Time Series Methods and Applications讀者反饋學(xué)科排名

一大塊

Acetaminophen

Catching Uncertainty of Wind: A Blend of Sieve Bootstrap and Regime Switching Models for Probabilisegime switching models. Our new bootstrapped regime switching (BRS) model delivers highly competitive, sharp and calibrated ensembles of wind speed forecasts, governed by various states of wind direction, and imposes minimal requirements on the observed wind data. The proposed methodology is illustr

Bricklayer

Addictive

不自然

舊式步槍

alliance

,A Brief Derivation of the Asymptotic Distribution of Pearson’s Statistic and an Accurate Approximattribution is introduced as an accurate approximation to be utilized when the chi-squared distribution proves to be inadequate. It is also explained that the exact probability mass function of this test statistic can be readily determined from its moment-generating function via symbolic computations. Two illustrative numerical examples are included.

邊緣帶來墨水

The Doubly Adaptive LASSO for Vector Autoregressive Models,lation matrix function (Heyse, 1985, [.]) and Yule–Walker or ordinary least squares estimates of a vector time series. The existing papers ignore the partial lag autocorrelation information inherent in a VAR process. The procedure shows promising results for VAR models. The procedure excels in terms of VAR lag order identification.

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