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Let be a sequence of real-valued random
variables and be other
random variables which are independent
of the form sequence. Suppose that are pairwise generalized negatively
orthant dependent with heavy tails under the condition that are
independent or associated, some asymptotic formulas are established.
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In this paper, we estimate parameters of gamma life distribution
and normal life distribution by EM algorithm based on Type-II hybrid censored data. The
covariance matrices are derived as well. Some numerical examples are also presented for
illustration.
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In this paper, we concern with the estimation problem for the Pareto
distribution based on progressive Type-II interval censoring with random removals. We discuss
the maximum likelihood estimation of the model parameters. Then, we show the consistency and
asymptotic normality of maximum likelihood estimators based on progressive Type-II interval
censored sample.
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Under inflation influence, this paper investigate a stochastic
differential game with reinsurance and investment. Insurance company chose a strategy
to minimizing the variance of the final wealth, and the financial markets as a game
``virtual hand'' chosen a probability measure represents the economic ``environment''
to maximize the variance of the final wealth. Through this double game between the
insurance companies and the financial markets, get optimal portfolio strategies. When
investing, we consider inflation, the method of dealing with inflation is: Firstly,
the inflation is converted to the risky assets, and then constructs the wealth process.
Through change the original based on the mean-variance criteria stochastic differential
game into unrestricted cases, then application linear-quadratic control theory obtain
optimal reinsurance strategy and investment strategy and optimal market strategy as well
as the closed form expression of efficient frontier are obtained; finally get reinsurance
strategy and optimal investment strategy and optimal market strategy as well as the
closed form expression of efficient frontier for the original stochastic differential game.
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A Bayesian semiparametric procedure for confirmatory factor analysis
model is proposed to address the heterogeneity of the multivariate responses. The approach
relies on the use of a prior over the space of mixing distributions with finite components.
Blocked Gibbs sampler is implemented to cope with the posterior analysis. For model comparison,
the measure and Bayes factor are developed. A generalized weighted Chinese restaurant
algorithm is suggested to compute the likelihood of data. Empirical results are presented to
illustrate the effectiveness of the methodologies.
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In this paper, we prove the existence and uniqueness of solutions
for reflected backward stochastic differential equations driven by a
Levy process, in which the reflecting barriers are just right
continuous with left limits whose jumps are arbitrary. To derive the
above results, the monotonic limit theorem of Backward SDE
associated with Levy process is established.
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Traditional claims reserve approaches are all based on aggregated
data and usually produce inaccurate projections of the reserve because the aggregated data
make a great loss of information contained in individual claims. Thus, the researcher in
actuarial science developed the so-called individual claim models that are based on marked
Poisson processes. However, due to the inappropriateness of Poisson distribution in
modelling the claims distributions, the present paper propose marked Cox processes as
reserve models. Compared with the aggregate claims models, the models proposed in the
current paper take more sufficient use of information contained in data and can be expected
to produce more accurate evaluations in claim loss reserving.
