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Bayesian Bivariate Cure Rate Models Using Copula Functions

Jie Huang, Haiming Zhou, Nader Ebrahimi
2022 International Journal of Statistics and Probability  
(FGM) copula function is applied to model the dependence structure of bivariate survival times.  ...  For the survival model fitting, DIC and LPML are used for model comparison. We perform a goodness-of-fit test for the new copula.  ...  Gallardo, Gómez, and de Castro (2018) proposed a cure rate model and applied the competing risks approach to the latent causes of the event of interest.  ... 
doi:10.5539/ijsp.v11n3p9 fatcat:stob265cfzhrhkjmit25x3662m

A New lifetime model for multivariate survival data with a surviving fraction

Vicente G. Cancho, Francisco Louzada, Dipak K. Dey, Gladys D.C. Barriga
2015 Journal of Statistical Computation and Simulation  
We develop this model assuming that there are m types of unobservable competing risks, where each risk is related to a time of the occurrence of an event of interest.  ...  In this paper we propose a new lifetime model for multivariate survival data with a surviving fraction.  ...  We compare the fitting of the BCR model with bivariate long-term distribution based on the Farlie-Gumbel-Morgenstern (FGM) copula model [16] with Weibull mixture marginal distributions by considering  ... 
doi:10.1080/00949655.2015.1007983 fatcat:mcvx5v5ikreqtiiaxjma7g2w4m

A copula-based approach to accommodate residential self-selection effects in travel behavior modeling

Chandra R. Bhat, Naveen Eluru
2009 Transportation Research Part B: Methodological  
The copula-based approach retains a parametric specification for the bivariate dependency, but allows testing of several parametric structures to characterize the dependency.  ...  The approach is based on the concept of a "copula", which is a multivariate functional form for the joint distribution of random variables derived purely from pre-specified parametric marginal distributions  ...  The authors are grateful to Lisa Macias for her help in formatting this document.  ... 
doi:10.1016/j.trb.2009.02.001 fatcat:vkubzfccgrfjra4lkx6y7jbfwq

Multivariate Survival Modelling: A Unified Approach with Copulas

Pierre Georges, Arnaud-Guilhem Lamy, Emeric Nicolas, Guillaume Quibel, Thierry Roncalli
2001 Social Science Research Network  
In this paper, we review the use of copulas for multivariate survival modelling.  ...  We derive the distribution of the failure time and order statistics.  ...  Then, we consider the modelling of competing risks. In particular, we derive the distribution of the failure time and other order statistics. Section fourth presents statistical inference.  ... 
doi:10.2139/ssrn.1032559 fatcat:bklici2ibvdydfb46hbhkrweke

Panel Data Methods and Applications to Health Economics [chapter]

Andrew M. Jones
2009 Palgrave Handbook of Econometrics  
These include conditional estimators, maximum simulated likelihood, Bayesian MCMC, finite mixtures and copulas.  ...  Models for longitudinal data 5.1 Applications of linear models 5.2 Applications with categorical outcomes 5.3 Applications with count data 5.4 Applications of quantile regression and other semiparametric  ...  These tests favour the FGM over the bivariate normal copula in terms of goodness of fit.  ... 
doi:10.1057/9780230244405_12 fatcat:4k3cr7zqwnegrdxaqm226mwj54

Papers from Actuarial Journals Worldwide

2011 Annals of Actuarial Science  
The rows of the triangle are stacked, resulting in a univariate time series with several missing values.  ...  Our conditions allow for risks that are not bounded, and we show that the most standard models satisfy our set of sufficient conditions, which are thus not restrictive.  ...  Risk models based on time series for count random variables. 19-28.  ... 
doi:10.1017/s174849951100025x fatcat:6uzk4t46vzcj5ltcqxbuvsv4km

Bayesian Models for Joint Longitudinal and Multi-State Survival Data [article]

Allison Furgal, University, My
With that motivation for our future projects, we work under the assumption that each risk has a latent failure time for each individual.  ...  We develop Bayesian joint models for longitudinal and competing risks survival data. A seldom considered aspect of competing risk joint models is the relationship between the two competing outcomes.  ...  Formulation of Dependence We will develop our models for the competing risks data under a latent failure time framework similar to the previous chapter.  ... 
doi:10.7302/2704 fatcat:ww2oo3eknbcn5d5xqik74ztag4

Four essays on linear and extreme dependences in credit derivatives and equity markets

Hendrik Supper, Technische Universität Dortmund, Technische Universität Dortmund
The chapter analyzes the linear and extreme dependence between stock prices, stock liquidity, and credit risk using a dynamic vine copula model and proposes a liquidity- and credit-adjusted Value-at-Risk  ...  co-movements in its CDS premia together with the market is priced in the bank's default swap spread during the recent financial crisis.  ...  We discuss the most important properties and show the (log) likelihoods for statistical inference.  ... 
doi:10.17877/de290r-6526 fatcat:42ur6xxanjgf7pc52cll5elgja

Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstracts

Mariagiulia Matteucci
We have developed a new algorithm for estimating the parameters of the mixture model described above.  ...  Support from the Institute of Statistical Science at Academia Sinica for a 3-week visit to collaborate with Dr. F.-S. Chai is also gratefully acknowledged.  ...  For models involving additional, fully observed, covariates we propose either the use of the generalized gamma accelerated failure time regression or an extension of the CNS method under the proportional  ... 
doi:10.6092/unibo/amsacta/3677 fatcat:3c3ua63y5jgl5drpjxd3qwo5yi