Bidimensional discrete-time risk models based on bivariate claim count time series
نویسندگان
چکیده
منابع مشابه
Count Time Series Models
We review regression models for count time series. We discuss the approach which is based on generalized linear models and the class of integer autoregressive processes. The generalized linear models framework provides convenient tools for implementing model fitting and prediction using standard software. Furthermore, this approach provides a natural extension to the traditional ARMA methodolog...
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چکیده ندارد.
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This paper proposes a discrete-time risk model that has a centain type of correlation between premiums and claim amounts. It is motivated by the well-known No Claims Discount system or bonus-malus system in the car insurance industry. Such a system penalises policyholders at fault in accidents by surcharges, and rewards claim-free years by discounts. For simplicity, only two levels of premium a...
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In Hidden Markov Models (HMM) the probability distribution of response Yt (∀t = 1, 2, . . . , T ) at each observation time is conditionally specified on the current hidden or latent state Xt. The sequence of hidden states follows a first order time-homogeneous Markov chain. Discrete time or continuous time HMM are respectively specified by T ⊆ N or T ⊆ R (from now on DHMM and CHMM). In this wor...
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Abstract. Count data over time are observed in many application areas. Many researchers use time series patterns to analyze this data. In this paper, the poisson count time series linear models and negative binomials on this type of data with the explanatory variables are studied. The Likelihood analysis and the evaluation of count time series model based on generalized linear models are pres...
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ژورنال
عنوان ژورنال: Journal of Inequalities and Applications
سال: 2015
ISSN: 1029-242X
DOI: 10.1186/s13660-015-0618-3