Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$
Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood est...
Ausführliche Beschreibung
Autor*in: |
Haiyan Xuan [verfasserIn] Lixin Song [verfasserIn] Un Cig Ji [verfasserIn] Yan Sun [verfasserIn] Tianjiao Dai [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2018 |
---|
Schlagwörter: |
Double AR ( p ) $\operatorname{AR}(p)$ model |
---|
Übergeordnetes Werk: |
In: Journal of Inequalities and Applications - SpringerOpen, 2002, (2018), 1, Seite 11 |
---|---|
Übergeordnetes Werk: |
year:2018 ; number:1 ; pages:11 |
Links: |
---|
DOI / URN: |
10.1186/s13660-018-1769-9 |
---|
Katalog-ID: |
DOAJ040560090 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ040560090 | ||
003 | DE-627 | ||
005 | 20230308040218.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230227s2018 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1186/s13660-018-1769-9 |2 doi | |
035 | |a (DE-627)DOAJ040560090 | ||
035 | |a (DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
050 | 0 | |a QA1-939 | |
100 | 0 | |a Haiyan Xuan |e verfasserin |4 aut | |
245 | 1 | 0 | |a Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ |
264 | 1 | |c 2018 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. | ||
650 | 4 | |a Double AR ( p ) $\operatorname{AR}(p)$ model | |
650 | 4 | |a Quasi-maximum exponential likelihood estimator | |
650 | 4 | |a Portmanteau test | |
650 | 4 | |a Autocorrelations | |
653 | 0 | |a Mathematics | |
700 | 0 | |a Lixin Song |e verfasserin |4 aut | |
700 | 0 | |a Un Cig Ji |e verfasserin |4 aut | |
700 | 0 | |a Yan Sun |e verfasserin |4 aut | |
700 | 0 | |a Tianjiao Dai |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t Journal of Inequalities and Applications |d SpringerOpen, 2002 |g (2018), 1, Seite 11 |w (DE-627)320977056 |w (DE-600)2028512-7 |x 1029242X |7 nnns |
773 | 1 | 8 | |g year:2018 |g number:1 |g pages:11 |
856 | 4 | 0 | |u https://doi.org/10.1186/s13660-018-1769-9 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100 |z kostenfrei |
856 | 4 | 0 | |u http://link.springer.com/article/10.1186/s13660-018-1769-9 |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/1029-242X |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_206 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_370 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2005 | ||
912 | |a GBV_ILN_2009 | ||
912 | |a GBV_ILN_2011 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_2027 | ||
912 | |a GBV_ILN_2055 | ||
912 | |a GBV_ILN_2111 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4326 | ||
912 | |a GBV_ILN_4335 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |j 2018 |e 1 |h 11 |
author_variant |
h x hx l s ls u c j ucj y s ys t d td |
---|---|
matchkey_str |
article:1029242X:2018----::usmxmmxoetalklhoetmtrnprmneuetfoberoeaonmapoebsd |
hierarchy_sort_str |
2018 |
callnumber-subject-code |
QA |
publishDate |
2018 |
allfields |
10.1186/s13660-018-1769-9 doi (DE-627)DOAJ040560090 (DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100 DE-627 ger DE-627 rakwb eng QA1-939 Haiyan Xuan verfasserin aut Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. Double AR ( p ) $\operatorname{AR}(p)$ model Quasi-maximum exponential likelihood estimator Portmanteau test Autocorrelations Mathematics Lixin Song verfasserin aut Un Cig Ji verfasserin aut Yan Sun verfasserin aut Tianjiao Dai verfasserin aut In Journal of Inequalities and Applications SpringerOpen, 2002 (2018), 1, Seite 11 (DE-627)320977056 (DE-600)2028512-7 1029242X nnns year:2018 number:1 pages:11 https://doi.org/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100 kostenfrei http://link.springer.com/article/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/toc/1029-242X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018 1 11 |
spelling |
10.1186/s13660-018-1769-9 doi (DE-627)DOAJ040560090 (DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100 DE-627 ger DE-627 rakwb eng QA1-939 Haiyan Xuan verfasserin aut Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. Double AR ( p ) $\operatorname{AR}(p)$ model Quasi-maximum exponential likelihood estimator Portmanteau test Autocorrelations Mathematics Lixin Song verfasserin aut Un Cig Ji verfasserin aut Yan Sun verfasserin aut Tianjiao Dai verfasserin aut In Journal of Inequalities and Applications SpringerOpen, 2002 (2018), 1, Seite 11 (DE-627)320977056 (DE-600)2028512-7 1029242X nnns year:2018 number:1 pages:11 https://doi.org/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100 kostenfrei http://link.springer.com/article/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/toc/1029-242X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018 1 11 |
allfields_unstemmed |
10.1186/s13660-018-1769-9 doi (DE-627)DOAJ040560090 (DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100 DE-627 ger DE-627 rakwb eng QA1-939 Haiyan Xuan verfasserin aut Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. Double AR ( p ) $\operatorname{AR}(p)$ model Quasi-maximum exponential likelihood estimator Portmanteau test Autocorrelations Mathematics Lixin Song verfasserin aut Un Cig Ji verfasserin aut Yan Sun verfasserin aut Tianjiao Dai verfasserin aut In Journal of Inequalities and Applications SpringerOpen, 2002 (2018), 1, Seite 11 (DE-627)320977056 (DE-600)2028512-7 1029242X nnns year:2018 number:1 pages:11 https://doi.org/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100 kostenfrei http://link.springer.com/article/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/toc/1029-242X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018 1 11 |
allfieldsGer |
10.1186/s13660-018-1769-9 doi (DE-627)DOAJ040560090 (DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100 DE-627 ger DE-627 rakwb eng QA1-939 Haiyan Xuan verfasserin aut Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. Double AR ( p ) $\operatorname{AR}(p)$ model Quasi-maximum exponential likelihood estimator Portmanteau test Autocorrelations Mathematics Lixin Song verfasserin aut Un Cig Ji verfasserin aut Yan Sun verfasserin aut Tianjiao Dai verfasserin aut In Journal of Inequalities and Applications SpringerOpen, 2002 (2018), 1, Seite 11 (DE-627)320977056 (DE-600)2028512-7 1029242X nnns year:2018 number:1 pages:11 https://doi.org/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100 kostenfrei http://link.springer.com/article/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/toc/1029-242X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018 1 11 |
allfieldsSound |
10.1186/s13660-018-1769-9 doi (DE-627)DOAJ040560090 (DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100 DE-627 ger DE-627 rakwb eng QA1-939 Haiyan Xuan verfasserin aut Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. Double AR ( p ) $\operatorname{AR}(p)$ model Quasi-maximum exponential likelihood estimator Portmanteau test Autocorrelations Mathematics Lixin Song verfasserin aut Un Cig Ji verfasserin aut Yan Sun verfasserin aut Tianjiao Dai verfasserin aut In Journal of Inequalities and Applications SpringerOpen, 2002 (2018), 1, Seite 11 (DE-627)320977056 (DE-600)2028512-7 1029242X nnns year:2018 number:1 pages:11 https://doi.org/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100 kostenfrei http://link.springer.com/article/10.1186/s13660-018-1769-9 kostenfrei https://doaj.org/toc/1029-242X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018 1 11 |
language |
English |
source |
In Journal of Inequalities and Applications (2018), 1, Seite 11 year:2018 number:1 pages:11 |
sourceStr |
In Journal of Inequalities and Applications (2018), 1, Seite 11 year:2018 number:1 pages:11 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Double AR ( p ) $\operatorname{AR}(p)$ model Quasi-maximum exponential likelihood estimator Portmanteau test Autocorrelations Mathematics |
isfreeaccess_bool |
true |
container_title |
Journal of Inequalities and Applications |
authorswithroles_txt_mv |
Haiyan Xuan @@aut@@ Lixin Song @@aut@@ Un Cig Ji @@aut@@ Yan Sun @@aut@@ Tianjiao Dai @@aut@@ |
publishDateDaySort_date |
2018-01-01T00:00:00Z |
hierarchy_top_id |
320977056 |
id |
DOAJ040560090 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ040560090</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230308040218.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s13660-018-1769-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ040560090</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QA1-939</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Haiyan Xuan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Double AR ( p ) $\operatorname{AR}(p)$ model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quasi-maximum exponential likelihood estimator</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Portmanteau test</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Autocorrelations</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Mathematics</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lixin Song</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Un Cig Ji</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yan Sun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Tianjiao Dai</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Journal of Inequalities and Applications</subfield><subfield code="d">SpringerOpen, 2002</subfield><subfield code="g">(2018), 1, Seite 11</subfield><subfield code="w">(DE-627)320977056</subfield><subfield code="w">(DE-600)2028512-7</subfield><subfield code="x">1029242X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">year:2018</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:11</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1186/s13660-018-1769-9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://link.springer.com/article/10.1186/s13660-018-1769-9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1029-242X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="j">2018</subfield><subfield code="e">1</subfield><subfield code="h">11</subfield></datafield></record></collection>
|
callnumber-first |
Q - Science |
author |
Haiyan Xuan |
spellingShingle |
Haiyan Xuan misc QA1-939 misc Double AR ( p ) $\operatorname{AR}(p)$ model misc Quasi-maximum exponential likelihood estimator misc Portmanteau test misc Autocorrelations misc Mathematics Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ |
authorStr |
Haiyan Xuan |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)320977056 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut aut aut |
collection |
DOAJ |
remote_str |
true |
callnumber-label |
QA1-939 |
illustrated |
Not Illustrated |
issn |
1029242X |
topic_title |
QA1-939 Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ Double AR ( p ) $\operatorname{AR}(p)$ model Quasi-maximum exponential likelihood estimator Portmanteau test Autocorrelations |
topic |
misc QA1-939 misc Double AR ( p ) $\operatorname{AR}(p)$ model misc Quasi-maximum exponential likelihood estimator misc Portmanteau test misc Autocorrelations misc Mathematics |
topic_unstemmed |
misc QA1-939 misc Double AR ( p ) $\operatorname{AR}(p)$ model misc Quasi-maximum exponential likelihood estimator misc Portmanteau test misc Autocorrelations misc Mathematics |
topic_browse |
misc QA1-939 misc Double AR ( p ) $\operatorname{AR}(p)$ model misc Quasi-maximum exponential likelihood estimator misc Portmanteau test misc Autocorrelations misc Mathematics |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Journal of Inequalities and Applications |
hierarchy_parent_id |
320977056 |
hierarchy_top_title |
Journal of Inequalities and Applications |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)320977056 (DE-600)2028512-7 |
title |
Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ |
ctrlnum |
(DE-627)DOAJ040560090 (DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100 |
title_full |
Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ |
author_sort |
Haiyan Xuan |
journal |
Journal of Inequalities and Applications |
journalStr |
Journal of Inequalities and Applications |
callnumber-first-code |
Q |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2018 |
contenttype_str_mv |
txt |
container_start_page |
11 |
author_browse |
Haiyan Xuan Lixin Song Un Cig Ji Yan Sun Tianjiao Dai |
class |
QA1-939 |
format_se |
Elektronische Aufsätze |
author-letter |
Haiyan Xuan |
doi_str_mv |
10.1186/s13660-018-1769-9 |
author2-role |
verfasserin |
title_sort |
quasi-maximum exponential likelihood estimator and portmanteau test of double ar(p) $\operatorname{ar}(p)$ model based on laplace(a,b) $\operatorname{laplace}(a,b)$ |
callnumber |
QA1-939 |
title_auth |
Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ |
abstract |
Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. |
abstractGer |
Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. |
abstract_unstemmed |
Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 |
container_issue |
1 |
title_short |
Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$ |
url |
https://doi.org/10.1186/s13660-018-1769-9 https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100 http://link.springer.com/article/10.1186/s13660-018-1769-9 https://doaj.org/toc/1029-242X |
remote_bool |
true |
author2 |
Lixin Song Un Cig Ji Yan Sun Tianjiao Dai |
author2Str |
Lixin Song Un Cig Ji Yan Sun Tianjiao Dai |
ppnlink |
320977056 |
callnumber-subject |
QA - Mathematics |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.1186/s13660-018-1769-9 |
callnumber-a |
QA1-939 |
up_date |
2024-07-03T15:30:51.717Z |
_version_ |
1803572374901096448 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ040560090</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230308040218.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s13660-018-1769-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ040560090</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJbe4afd5ff94c469f85c6130a9d782100</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QA1-939</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Haiyan Xuan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Quasi-maximum exponential likelihood estimator and portmanteau test of double AR(p) $\operatorname{AR}(p)$ model based on Laplace(a,b) $\operatorname{Laplace}(a,b)$</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{AR}(p)$ model with Laplace(a,b) $\operatorname{Laplace}(a,b)$ distribution. The double AR(p) $\operatorname{AR}(p)$ model is investigated to propose firstly the quasi-maximum exponential likelihood estimator, design a portmanteau test of double AR(p) $\operatorname{AR}(p)$ on the basis of autocorrelation function, and then establish some asymptotic results. Finally, an empirical study shows that the estimation and the portmanteau test obtained in this paper are very feasible and more effective.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Double AR ( p ) $\operatorname{AR}(p)$ model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quasi-maximum exponential likelihood estimator</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Portmanteau test</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Autocorrelations</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Mathematics</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lixin Song</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Un Cig Ji</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yan Sun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Tianjiao Dai</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Journal of Inequalities and Applications</subfield><subfield code="d">SpringerOpen, 2002</subfield><subfield code="g">(2018), 1, Seite 11</subfield><subfield code="w">(DE-627)320977056</subfield><subfield code="w">(DE-600)2028512-7</subfield><subfield code="x">1029242X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">year:2018</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:11</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1186/s13660-018-1769-9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/be4afd5ff94c469f85c6130a9d782100</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://link.springer.com/article/10.1186/s13660-018-1769-9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1029-242X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="j">2018</subfield><subfield code="e">1</subfield><subfield code="h">11</subfield></datafield></record></collection>
|
score |
7.401552 |