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010   $a981-16-2264-7
024 7 $a10.1007/978-981-16-2264-9
035   $a(CKB)4100000011954465
035   $a(DE-He213)978-981-16-2264-9
035   $a(MiAaPQ)EBC6639207
035   $a(Au-PeEL)EBL6639207
035   $a(OCoLC)1256242018
035   $a(PPN)258061316
035   $a(EXLCZ)994100000011954465
100   $a20210608d2021      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aDiagnostic Methods in Time Series /$fby Fumiya Akashi, Masanobu Taniguchi, Anna Clara Monti, Tomoyuki Amano
205   $a1st ed. 2021.
210  1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2021.
215   $a1 online resource (X, 108 p. 17 illus., 10 illus. in color.)
225 1 $aJSS Research Series in Statistics,$x2364-0065
311 08$a981-16-2263-9 
320   $aIncludes bibliographical references and index.
327   $aChapter 1. Elements of Stochastic Processes -- Chapter 2. Systematic approach for portmanteau tests in view of Whittle likelihood ratio -- Chapter 3. A new look at portmanteau test -- Chapter 4. Adjustments for a class of tests under nonstandard conditions -- Chapter 5. Adjustments for variance component tests in ANOVA models -- Chapter 6. Robust causality test of infinite variance processes.
330   $aThis book contains new aspects of model diagnostics in time series analysis, including variable selection problems and higher-order asymptotics of tests. This is the first book to cover systematic approaches and widely applicable results for nonstandard models including infinite variance processes. The book begins by introducing a unified view of a portmanteau-type test based on a likelihood ratio test, useful to test general parametric hypotheses inherent in statistical models. The conditions for the limit distribution of portmanteau-type tests to be asymptotically pivotal are given under general settings, and very clear implications for the relationships between the parameter of interest and the nuisance parameter are elucidated in terms of Fisher-information matrices. A robust testing procedure against heavy-tailed time series models is also constructed in the context of variable selection problems. The setting is very reasonable in the context of financial data analysis and econometrics, and the result is applicable to causality tests of heavy-tailed time series models. In the last two sections, Bartlett-type adjustments for a class of test statistics are discussed when the parameter of interest is on the boundary of the parameter space. A nonlinear adjustment procedure is proposed for a broad range of test statistics including the likelihood ratio, Wald and score statistics.
410  0$aJSS Research Series in Statistics,$x2364-0065
606   $aStatistics
606   $aStatistics
606   $aTime-series analysis
606   $aStatistical Theory and Methods
606   $aApplied Statistics
606   $aStatistics in Business, Management, Economics, Finance, Insurance
606   $aTime Series Analysis
615  0$aStatistics.
615  0$aStatistics.
615  0$aTime-series analysis.
615 14$aStatistical Theory and Methods.
615 24$aApplied Statistics.
615 24$aStatistics in Business, Management, Economics, Finance, Insurance.
615 24$aTime Series Analysis.
676   $a519.55
700   $aAkashi$b Fumiya$0767971
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483157503321
996   $aDiagnostic Methods in Time Series$91905068
997   $aUNINA