This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations. Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.
具體描述
讀後感
評分
評分
評分
評分
用戶評價
學術味還是太濃瞭，作者大約在 diffuse initialization 上有專長，四處見縫插針。
评分學術味還是太濃瞭，作者大約在 diffuse initialization 上有專長，四處見縫插針。
评分傳說中綽號DK的就是此書……
评分傳說中綽號DK的就是此書……
评分傳說中綽號DK的就是此書……
相關圖書
本站所有內容均為互聯網搜索引擎提供的公開搜索信息，本站不存儲任何數據與內容，任何內容與數據均與本站無關，如有需要請聯繫相關搜索引擎包括但不限於百度，google,bing,sogou 等
© 2025 qciss.net All Rights Reserved. 小哈圖書下載中心 版权所有