國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Diagnostic methods in time series

Akashi, Fumiya.

Diagnostic methods in time series

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Diagnostic methods in time seriesby Fumiya Akashi ... [et al.].
其他作者:	Akashi, Fumiya.
出版者:	Singapore :Springer Singapore :2021.
面頁冊數:	x, 108 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Time-series analysis.
電子資源:	https://doi.org/10.1007/978-981-16-2264-9
ISBN:	9789811622649$q(electronic bk.)

Diagnostic methods in time series
Diagnostic methods in time series[electronic resource] /by Fumiya Akashi ... [et al.]. - Singapore :Springer Singapore :2021. - x, 108 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in statistics. JSS research series in statistics. - SpringerBriefs in statistics.JSS research series in statistics..

Chapter 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.

This 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.

ISBN: 9789811622649$q(electronic bk.)

Standard No.: 10.1007/978-981-16-2264-9doiSubjects--Topical Terms:

181890
Time-series analysis.

LC Class. No.: QA280

Dewey Class. No.: 519.55

Diagnostic methods in time series
LDR:02851nmm a2200337 a 4500 001 602493
003 DE-He213
005 20210617015630.0
006 m d
007 cr nn 008maaau
008 211112s2021 si s 0 eng d
020 $a 9789811622649$q(electronic bk.)
020 $a 9789811622632$q(paper)
024 7 $a 10.1007/978-981-16-2264-9 $2 doi
035 $a 978-981-16-2264-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QA280
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.55 $2 23
090 $a QA280 $b .D536 2021
245 0 0 $a Diagnostic methods in time series $h [electronic resource] / $c by Fumiya Akashi ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a x, 108 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in statistics. JSS research series in statistics
505 0 $a Chapter 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.
520 $a This 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.
650 0 $a Time-series analysis. $3 181890
650 1 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Applied Statistics. $3 805583
650 2 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 825914
700 1 $a Akashi, Fumiya. $3 825938
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs in statistics. $p JSS research series in statistics. $3 829180
856 4 0 $u https://doi.org/10.1007/978-981-16-2264-9
950 $a Mathematics and Statistics (SpringerNature-11649)