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Multivariate negative binomial models for insurance claim counts

Peng Shi, Emiliano A. Valdez
2014 Insurance, Mathematics & Economics  
The first one works with the discrete count data directly using a mixture of max-id copulas that allows for flexible pair-wise association as well as tail and global dependence.  ...  the discrete count data directly using a mixture of max-id copulas. • The second one employs elliptical copulas to join continuitized count data. • We show the advantage of the copula approach over the  ...  Emiliano also wishes to extend his appreciation for the participants of the Non-Gaussian Multivariate Statistical Models workshop held at the Banff International Research Station in May 2013, for their  ... 
doi:10.1016/j.insmatheco.2013.11.011 fatcat:22f3myd3gjfkthqwowpexnsxpa

A Copulas-Based Approach to Modeling Dependence in Decision Trees

Tianyang Wang, James S. Dyer
2012 Operations Research  
This paper presents a general framework based on copulas for modeling dependent multivariate uncertainties through the use of a decision tree.  ...  While this approach to modeling dependencies can be based on several popular copula families as we illustrate, we focus on the use of the normal copula and present an efficient computational method for  ...  The authors acknowledge support from the Center for Petroleum Asset Risk Management at the University of Texas at Austin.  ... 
doi:10.1287/opre.1110.1004 fatcat:357wml45ijgkvcfk3j3hwftpvi

Dependence modeling of multivariate longitudinal hybrid insurance data with dropout

Edward W. Frees, Catalina Bolancé, Montserrat Guillen, Emiliano A. Valdez
2021 Expert systems with applications  
This paper introduces a generalized method of moments technique to estimate dependence parameters where associations are represented using copulas. This is especially useful for large data sets.  ...  Insurance claims outcomes are also naturally a hybrid with both discrete and continuous components, which adds complexity to model calibration.  ...  Acknowledgments C.B. and M.G. thank the Spanish Ministry of Science, grant PID2019-105986GB-C21-M.G. thanks ICREA Academia.  ... 
doi:10.1016/j.eswa.2021.115552 fatcat:jwkg4x5ndjadngjjxsmbqhj4ba

Semi-parametric copula sample selection models for count responses

Giampiero Marra, Karol Wyszynski
2016 Computational Statistics & Data Analysis  
Sample selection models for count data which allow for the use of potentially any discrete distribution, non-Gaussian dependencies between the selection and outcome equations, and flexible covariate effects  ...  While sample selection models for continuous and binary outcomes have been widely studied in the literature, the case of count response has not received as much attention.  ...  The authors would also like to thank Christian Hennig, Rosalba Radice and Dr Ma lgorzata Wojtyś for many useful discussions on the preliminary versions of this work.  ... 
doi:10.1016/j.csda.2016.06.003 fatcat:c4fjlhkhrne4xlvfk4b2bsvqpe

Multivariate Frequency-Severity Regression Models in Insurance

Edward Frees, Gee Lee, Lu Yang
2016 Risks  
This paper contributes to this body of literature by focusing on the use of a copula for modeling the dependence among these outcomes; a major advantage of this tool is that it preserves the body of work  ...  Regression models for understanding the distribution of each outcome continue to be developed yet there now exists a solid body of literature for the marginal outcomes.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/risks4010004 fatcat:3st2oepcpbbm3kxsk5yauovuty

Multilevel modeling of insurance claims using copulas

Peng Shi, Xiaoping Feng, Jean-Philippe Boucher
2016 Annals of Applied Statistics  
To capture the unique features of policy-level insurance costs, we propose a copula regression for the multivariate longitudinal claims.  ...  In the model, the Tweedie double generalized linear model is employed to examine the semi-continuous claim cost of each coverage type, and a Gaussian copula is specified to accommodate the cross-sectional  ...  The multilevel structure of claims are accommodated using dependence models. We use a Gaussian copula to join the mixed outcome of claim costs.  ... 
doi:10.1214/16-aoas914 fatcat:opxzvalfovbkvpmnq4swio64jq

Towards an improved critical wave groups method for the probabilistic assessment of large ship motions in irregular seas

Panayiotis A. Anastopoulos, Kostas J. Spyrou, Christopher C. Bassler, Vadim Belenky
2016 Probabilistic Engineering Mechanics  
The derived wave groups are intended to be used for the assessment of ship stability in irregular seas.  ...  A novel approach for the systematic construction of wind-generated, high probability, wave groups, is presented.  ...  On the other hand, the Clayton copula, with parameter c, is used for modeling dependence between the height and period encountered within a single wave:     1 , 1 . cc c C u v u v      (17) The  ... 
doi:10.1016/j.probengmech.2015.12.009 fatcat:54mdylkvhzbphowx57ov5zdrx4

Understanding Relationships Using Copulas

Edward W. Frees, Emiliano A. Valdez
1998 North American Actuarial Journal  
For those who wish to use copulas for statistical inference, we illustrate statistical inference procedures by using insurance company data on losses and expenses.  ...  This article introduces actuaries to the concept of "copulas," a tool for understanding relationships among multivariate outcomes.  ...  This paper uses copulas to define three nonparametric measures of dependence for pairs of random variables.  ... 
doi:10.1080/10920277.1998.10595667 fatcat:2gbsmifpljdedllk2rr24o5tpi

Construction Safety Risk Modeling and Simulation [article]

Antoine J.-P. Tixier, Matthew R. Hallowell, Balaji Rajagopalan
2016 arXiv   pre-print
construction safety calls for the accurate modeling, simulation, and assessment of safety risk.  ...  Our fully data-driven approach provides construction practitioners and academicians with an easy and automated way of extracting valuable empirical insights from databases of unstructured textual injury  ...  In our experiments, we used a threshold of 80%, (i.e., we computed Q(0.8) with the quantile() R function), but the choice of the threshold should be made at the discretion of the user, depending on the  ... 
arXiv:1609.07912v1 fatcat:fcvu3hshtrgm3kc5ytsu7hpfvu

Simultaneous equation penalized likelihood estimation of vehicle accident injury severity

Francesco Donat, Giampiero Marra
2018 Journal of the Royal Statistical Society, Series C: Applied Statistics  
Non-Gaussian error dependence structures are dealt with using Archimedean copulae, whose association parameter is also specified in terms of an additive predictor.  ...  The functional form of covariate effects is assumed fairly flexible with appropriate smoothers included in the model representation to account for non-linearities and spatial variability in the data.  ...  Data Analysis Our empirical study uses data from the "Bulletins d'Analyse des Accidents Corporels" (BAAC) 2014.  ... 
doi:10.1111/rssc.12267 fatcat:6rbperlqvbcrngtteaxv56ykaa

Dependence Structure and Risk Measure*

Thierry Ané, Cécile Kharoubi
2003 The journal of business  
However, one has to recognize the paucity of distributions that can be used as an aid for modeling the structure of multivariate data.  ...  III, namely, the FTSE 100-NASDAQ. for accident precursor analysis as well as in Frees and Valdez (1998) for the estimation of joint life mortality and multiple decrement models.  ... 
doi:10.1086/375253 fatcat:thm5q4mr7zbjlnaokmoxnjgtky

A Simulation-Based Approach to Decision Making with Partial Information

Luis V. Montiel, J. Eric Bickel
2012 Decision Analysis  
T he construction of a probabilistic model is a key step in most decision and risk analyses.  ...  The difficulty of this approach is that often the joint distribution is underspecified. For example, we may lack knowledge of the marginal distributions or the underlying dependence structure.  ...  Acknowledgments The authors thank Tianyang Wang, the associate editor, and two anonymous referees for their helpful comments and suggestions on a draft of this paper.  ... 
doi:10.1287/deca.1120.0252 fatcat:4txdrzsdrjazlmkqq46rdy324i

Dealing with Dependent Risks [chapter]

Claudia Klüppelberg, Robert Stelzer
2014 Risk - A Multidisciplinary Introduction  
The facts. • Dependence between risks and/or sources of risks are crucial for risk assessment, quantification and management.  ...  This may concern the time of their occurrence and/or their severity. In other words, we need to understand how to model and describe the dependence structure of risks.  ...  So the question arises whether the use of a copula is the best way to transform data. Alternative transformations are indeed used in relation to some special applications.  ... 
doi:10.1007/978-3-319-04486-6_9 fatcat:rc34j55cgvc6dmu2y4x5old4ae

A joint model for mode choice and escort decisions of school trips

Alireza Ermagun, Taha Hossein Rashidi, Amir Samimi
2014 Transportmetrica A: Transport Science  
Two modelling formulations are used: a nested logit (NL) model and a copula-based model. Results showed that the copula model outperforms the NL model.  ...  This study is the first effort to mathematically model the mode choice and accompaniment pattern selection by parents for the school trip of students, in a joint modelling structure as it is believed that  ...  Acknowledgements The authors wish to express their profound gratitude and deep regards to Shahrbanou Khaniki for her kind assistance in data collection.  ... 
doi:10.1080/23249935.2014.968654 fatcat:qsjvlqtt7rfphaioiptgqjysha


2012 Annals of Actuarial Science  
Single copies of all the papers listed here can be obtained, subject to charge and copyright regulations, from the Actuarial Profession's libraries. Issues may be borrowed by members.  ...  Dependence modeling in non-life insurance using the Bernstein copula. 430-436. This paper illustrates the modeling of dependence structures of nonlife insurance risks using the Bernstein copula.  ...  Dependent loss reserving using copulas. 449-486.  ... 
doi:10.1017/s1748499512000103 fatcat:q6oov4w3a5e3dochnvpezxcooe
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