1 resultado para Multivariate volatility models
em Dalarna University College Electronic Archive
Filtro por publicador
- KUPS-Datenbank - Universität zu Köln - Kölner UniversitätsPublikationsServer (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (2)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (3)
- Aquatic Commons (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (5)
- Aston University Research Archive (12)
- Biblioteca de Teses e Dissertações da USP (2)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (4)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (11)
- Biblioteca Digital de la Universidad Católica Argentina (1)
- Bioline International (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (13)
- Brock University, Canada (2)
- Brunel University (1)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- Bulgarian Digital Mathematics Library at IMI-BAS (3)
- Cambridge University Engineering Department Publications Database (4)
- CentAUR: Central Archive University of Reading - UK (23)
- Cochin University of Science & Technology (CUSAT), India (7)
- Collection Of Biostatistics Research Archive (8)
- CORA - Cork Open Research Archive - University College Cork - Ireland (4)
- Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest (1)
- Dalarna University College Electronic Archive (1)
- Deakin Research Online - Australia (41)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (2)
- Digital Commons - Michigan Tech (1)
- Digital Commons at Florida International University (3)
- Digital Peer Publishing (1)
- DigitalCommons@The Texas Medical Center (4)
- DRUM (Digital Repository at the University of Maryland) (2)
- Duke University (8)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (5)
- Glasgow Theses Service (1)
- Greenwich Academic Literature Archive - UK (2)
- Helda - Digital Repository of University of Helsinki (14)
- Indian Institute of Science - Bangalore - Índia (3)
- Instituto Gulbenkian de Ciência (1)
- Instituto Politécnico do Porto, Portugal (2)
- Massachusetts Institute of Technology (1)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (2)
- Publishing Network for Geoscientific & Environmental Data (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (13)
- Queensland University of Technology - ePrints Archive (617)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (24)
- Repositorio Institucional da UFLA (RIUFLA) (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional da Universidade Federal do Rio Grande do Norte (1)
- Repositório Institucional da Universidade Tecnológica Federal do Paraná (RIUT) (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (26)
- Repositorio Institucional Universidad de Medellín (2)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (2)
- Universidad de Alicante (1)
- Universidad del Rosario, Colombia (6)
- Universidad Politécnica de Madrid (4)
- Universidade Complutense de Madrid (6)
- Universidade Federal do Rio Grande do Norte (UFRN) (4)
- Universidade Técnica de Lisboa (2)
- Universitat de Girona, Spain (4)
- Université de Montréal (2)
- Université de Montréal, Canada (20)
- University of Connecticut - USA (3)
- University of Queensland eSpace - Australia (7)
- University of Washington (2)
- WestminsterResearch - UK (2)
Resumo:
This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.