Holdings: Analysis of latent Gaussian models with spatial dependence

Analysis of latent Gaussian models with spatial dependence:

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Bibliographic Details
Main Author:	Vogler, Jan (Author)
Format:	Thesis Book
Language:	English
Published:	Köln 2016
Subjects:	Ökonometrisches Modell Kriminalität Staat Räumliche Statistik Probabilistische Testtheorie Prognose Hochschulschrift
Online Access:	Inhaltsverzeichnis Inhaltsverzeichnis
Physical Description:	146 Seiten Diagramme, Karten

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MARC


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adam_text	C ONTENTS 1 INTRODUCTION 1 1.1 CONTRIBUTION AND O U TLIN E .............................................................................. 2 2 SPATIAL AUTOCORRELATION IN LINEAR SPATIAL MODELS 5 2.1 SPATIAL STOCHASTIC PROCESSES ....................................................................... 5 2.1.1 SPATIAL AUTOREGRESSIVE P RO C E S S ........................................................ 5 2.1.2 SPATIAL MOVING AVERAGE P R O C E S S ..................................................... 6 2.1.3 SPATIAL WEIGHT M ATRICES .................................................................... 6 2.1.4 CORRELATION STRUCTURE OF SPATIAL AUTOREGRESSIVE AND MOVING AV ERAGE P RO C E SSE S................................................................................. 7 2.2 LINEAR SPATIAL M ODELS.................................................................................... 8 2.3 ESTIMATION OF LINEAR SPATIAL M O D E LS ...........................................................10 2.4 SPARSE MATRIX TECHNIQUES FOR LARGE SA M P LE S .............................................. 15 3 SPATIAL LATENT GAUSSIAN MODELS 20 3.1 SPATIAL PROBIT M ODELS ....................................................................................... 21 3.2 SPATIAL COUNT DATA M O D E LS .............................................................................. 23 3.3 CENSORED DATA .................................................................................................25 3.4 INFERENCE IN SPATIAL LATENT GAUSSIAN M ODELS .............................................. 25 3.4.1 GENERALIZED METHOD OF MOMENTS AND COMPOSITE MARGINAL LIKE LIHOOD E STIM A TIO N ................................................................................. 26 3.4.2 MAXIMUM LIKELIHOOD ESTIM A TIO N ........................................................ 31 3.4.3 BAYESIAN ESTIMATION OF SPATIAL LATENT GAUSSIAN M ODELS.....................36 3.5 AUTO-MODELS: AN ALTERNATIVE TO LATENT GAUSSIAN M ODELS ......................... 40 4 MAXIMUM LIKELIHOOD ESTIMATION OF SPATIAL LATENT GAUSSIAN MODELS 43 4.1 SPATIAL DEPENDENT VARIABLE M O D E LS................................................................45 4.1.1 BASELINE M O D E L .................................................................................... 45 4.1.2 SPATIAL PROBIT M ODELS...........................................................................46 4.1.3 SPATIAL COUNT DATA M O D E LS ..................................................................47 4.1.4 CENSORED DATA .....................................................................................48 4.2 SPATIAL EIS ....................................................................................................... 48 4.2.1 EIS PRINCIPLE ........................................................................................49 4.2.2 SEQUENTIAL EIS .....................................................................................51 4.2.3 SEQUENTIAL EIS FOR SPATIAL M O D E LS ......................................................53 4.2.4 SPATIAL PROBIT M O D E L ........................................................................... 62 4.2.5 SPATIAL POISSON MODEL ....................................................................... 64 4.2.6 CENSORED DATA .....................................................................................65 4.3 MONTE CARLO S TU D Y ...........................................................................................65 4.3.1 SPATIAL PROBIT M ODELS ........................................................................... 67 4.3.2 SPATIAL POISSON M O D E LS........................................................................ 68 4.4 EMPIRICAL A PPLICATIONS.....................................................................................68 4.4.1 SPATIAL PROBIT FOR THE 1996 US PRESIDENTIAL E LE C TIO N ...................... 68 4.4.2 SPATIAL COUNT MODEL FOR US FIRMS LOCATION C H O IC E S ........................... 70 4.5 C ONCLUSIONS....................................................................................................... 71 4.6 TABLES AND F IG U RE S ........................................................................................... 73 5 COMPOSITE MARGINAL LIKELIHOOD ESTIMATION OF SPATIAL LATENT GAUSSIAN MODELS 79 5.1 SPATIAL DEPENDENT VARIABLE M O D E LS...............................................................80 5.2 COMPOSITE MARGINAL LIKELIHOOD A P P R O A C H ......................................................82 5.3 COMPUTATIONAL ISSU E S........................................................................................84 5.4 MONTE CARLO S T U D Y ...........................................................................................84 5.5 CONCLUSION...........................................................................................................87 5.6 T A B LE S .................................................................................................................88 6 A SPATIO-TEMPORAL PANEL COUNT MODEL FOR ANALYSIS AND PREDICTION OF URBAN CRIME 91 6.1 PREDICTORS AND DEPENDENCE IN TIME AND SPACE OF CRIME RA TE S ...................... 93 6.1.1 P RE D ICTO RS.............................................................................................. 93 6.1.2 SPATIAL DEPENDENCE .............................................................................. 94 6.1.3 TEMPORAL DEPENDENCE ........................................................................... 95 6.2 D A T A .................................................................................................................... 97 6.2.1 DATA SOURCES...........................................................................................97 6.2.2 SOME DESCRIPTIVE S TA TIS TIC S .................................................................. 98 6.3 SPATIO-TEMPORAL PANEL COUNT MODEL FOR C R IM E S ............................................ 98 6.3.1 MODEL SPECIFICATION..............................................................................98 6.3.2 STATIONARITY AND TIME-SPACE SEPARABILITY ....................................... 100 6.3.3 SPATIO-TEMPORAL EFFECTS OF THE COVARIATES .........................................101 6.4 EIS BASED LIKELIHOOD INFERENCE...................................................................... 103 6.4.1 LIKELIHOOD............................................................................................104 6.4.2 SPATIAL E I S .........................................................................................105 6.4.3 SMOOTHING AND P RE D ICTIO N ................................................................108 6.5 EMPIRICAL R E S U L T S ............................................................................................110 6.5.1 BASELINE M O D E L .................................................................................. I L L 6.5.2 RANDOM EFFECTS C O V A RIA TE S................................................................ 112 6.5.3 FULL M O D E L............................................................................................113 6.5.4 PREDICTIVE M O D E L ............................................................................... 115 6.6 C ONCLUSIONS..................................................................................................... 117 6.7 TABLES AND F IG U RE S .........................................................................................121 7 CONCLUSIONS 131
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author	Vogler, Jan
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format	Thesis Book
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spelling	Vogler, Jan Verfasser (DE-588)1017504687 aut Analysis of latent Gaussian models with spatial dependence vorgelegt von Dipl.-Volkswirt Jan Vogler Köln 2016 146 Seiten Diagramme, Karten txt rdacontent n rdamedia nc rdacarrier Dissertation Universität zu Köln 2016 Ökonometrisches Modell (DE-588)4043212-9 gnd rswk-swf Kriminalität (DE-588)4033178-7 gnd rswk-swf Staat (DE-588)4056618-3 gnd rswk-swf Räumliche Statistik (DE-588)4386767-4 gnd rswk-swf Probabilistische Testtheorie (DE-588)4496586-2 gnd rswk-swf Prognose (DE-588)4047390-9 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Räumliche Statistik (DE-588)4386767-4 s Staat (DE-588)4056618-3 s Kriminalität (DE-588)4033178-7 s Prognose (DE-588)4047390-9 s Ökonometrisches Modell (DE-588)4043212-9 s Probabilistische Testtheorie (DE-588)4496586-2 s DE-604 http://digitool.hbz-nrw.de:1801/webclient/DeliveryManager?pid=7123055&custom_att_2=simple_viewer Analysis of latent Gaussian models with spatial dependence Inhaltsverzeichnis DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029637311&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Vogler, Jan Analysis of latent Gaussian models with spatial dependence Ökonometrisches Modell (DE-588)4043212-9 gnd Kriminalität (DE-588)4033178-7 gnd Staat (DE-588)4056618-3 gnd Räumliche Statistik (DE-588)4386767-4 gnd Probabilistische Testtheorie (DE-588)4496586-2 gnd Prognose (DE-588)4047390-9 gnd
subject_GND	(DE-588)4043212-9 (DE-588)4033178-7 (DE-588)4056618-3 (DE-588)4386767-4 (DE-588)4496586-2 (DE-588)4047390-9 (DE-588)4113937-9
title	Analysis of latent Gaussian models with spatial dependence
title_auth	Analysis of latent Gaussian models with spatial dependence
title_exact_search	Analysis of latent Gaussian models with spatial dependence
title_full	Analysis of latent Gaussian models with spatial dependence vorgelegt von Dipl.-Volkswirt Jan Vogler
title_fullStr	Analysis of latent Gaussian models with spatial dependence vorgelegt von Dipl.-Volkswirt Jan Vogler
title_full_unstemmed	Analysis of latent Gaussian models with spatial dependence vorgelegt von Dipl.-Volkswirt Jan Vogler
title_short	Analysis of latent Gaussian models with spatial dependence
title_sort	analysis of latent gaussian models with spatial dependence
topic	Ökonometrisches Modell (DE-588)4043212-9 gnd Kriminalität (DE-588)4033178-7 gnd Staat (DE-588)4056618-3 gnd Räumliche Statistik (DE-588)4386767-4 gnd Probabilistische Testtheorie (DE-588)4496586-2 gnd Prognose (DE-588)4047390-9 gnd
topic_facet	Ökonometrisches Modell Kriminalität Staat Räumliche Statistik Probabilistische Testtheorie Prognose Hochschulschrift
url	http://digitool.hbz-nrw.de:1801/webclient/DeliveryManager?pid=7123055&custom_att_2=simple_viewer http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029637311&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT voglerjan analysisoflatentgaussianmodelswithspatialdependence

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