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Multivariate mixed normal conditional heteroskedasticity

Luc, BAUWENS; C.M., HAFNER; J.V.K., ROMBOUTS - Institut de Recherche Économique et Sociale (IRES), … - 2006

We propose a new multivariate volatility model where the conditional distribution of a vector time series is given by a mixture of multivariate normal distributions. Each of these distributions is allowed to have a time-varying covariance matrix. The process can be globally covariance-stationary...

Persistent link: https://www.econbiz.de/10004984765

On the Bayesian mixture of generalized linear models with gamma-distributed responses

Susanto, Irwan; Iriawan, Nur; Kuswanto, Heri - In: Econometrics : open access journal 10 (2022) 4, pp. 1-28

This paper proposes enhanced studies on a model consisting of a finite mixture framework of generalized linear models (GLMs) with gamma-distributed responses estimated using the Bayesian approach coupled with the Markov Chain Monte Carlo (MCMC) method. The log-link function, which relates the...

Persistent link: https://www.econbiz.de/10013533212

Empirical methods for the law

Engel, Christoph - 2017

To their credit, empirical legal scholars try to live up to the highest methodological standards from the social sciences. But these standards do not always match the legal research question. This paper focuses on normative legal argument based on empirical evidence. Whether there is a normative...

Persistent link: https://www.econbiz.de/10011645949

Dealing with misspecification in structural macroeconometric models

Canova, Fabio; Matthes, Christian - In: Quantitative economics : QE ; journal of the … 12 (2021) 2, pp. 313-350

We consider a set of potentially misspecified structural models, geometrically combine their likelihood functions, and estimate the parameters using composite methods. In a Monte Carlo study, composite estimators dominate likelihood-based estimators in mean squared error and composite models are...

Persistent link: https://www.econbiz.de/10012598417

Modelling preference heterogeneity using a Bayesian finite mixture of almost ideal demand systems

Kehlbacher, Ariane; Srinivasan, C. S.; McCloy, Rachel; … - In: European review of agricultural economics 47 (2020) 3, pp. 933-970

Persistent link: https://www.econbiz.de/10012257927

Rating frailty, Bayesian updates, and portfolio credit risk analysis

Bu, Shang; Guo, Nan; Li, Lingfei - In: Quantitative finance 22 (2022) 4, pp. 777-797

Persistent link: https://www.econbiz.de/10013367859

Generalised Lindley shared additive frailty regression model for bivariate survival data

Pandey, Arvind; Hanagal, David D.; Tyagi, Shikhar - In: Statistics in transition : an international journal of … 23 (2022) 4, pp. 161-176

Frailty models are the possible choice to counter the problem of the unobserved heterogeneity in individual risks of … disease and death. Based on earlier studies, shared frailty models can be utilised in the analysis of bivariate data related … to survival times (e.g. matched pairs experiments, twin or family data). In this article, we assume that frailty acts …

Persistent link: https://www.econbiz.de/10014287929

Bayesian analysis for step-stress accelerated life testing using weibull proportional hazard model

Sha, Naijun; Pan, Rong - In: Statistical Papers 55 (2014) 3, pp. 715-726

In this paper, we present a Bayesian analysis for the Weibull proportional hazard (PH) model used in step-stress accelerated life testings. The key mathematical and graphical difference between the Weibull cumulative exposure (CE) model and the PH model is illustrated. Compared with the CE...

Persistent link: https://www.econbiz.de/10010848037

Bonus-Malus systems with Weibull distributed claim severities

Ni, Weihong; Constantinescu, Corina; Pantelous, … - In: Annals of actuarial science : publ. by the Institute of … 8 (2014) 2, pp. 217-233

Persistent link: https://www.econbiz.de/10010422193

Weibull wind worth : wait and watch?

Lillestøl, Jostein - 2016

Persistent link: https://www.econbiz.de/10011422675