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 2012 Vol.28 Issue.6,Published 2012-12-16 article
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 561 Parameter Estimation for a Mixture of Generalized Exponential Distributions under Grouped and Right-Censored Samples Tian Yuzhu,Tian Maozai,Chen Ping Parameter estimation of mixed generalized exponential distribution model under grouped and right-censored data is considered by using EM algorithm in this paper. The estimation formulae are obtained and some simulations are presented to illustrate the proposed method. Finally, a set of medicine data is analyzed. 2012 Vol. 28 (6): 561-571 [Abstract] ( 932 ) [HTML 1KB] [ PDF 245KB] ( 1276 )
 572 Preliminary Test Two-Parameter Estimators Based on W, LR and LM Test-Statistics in a Regression Model Chang Xinfeng,Yang Hu In this paper, we proposed the preliminary test two-parameter estimators based on the Wald (W), the Likelihood Ration (LR) and the Lagrangian Multiplier (LM) tests, when it is suspected that the regression parameter may be restricted to a subspace. The bias and the mean square error (MSE) of the proposed estimators are derived and compared. The conditions of superiority of the proposed estimators are obtained. 2012 Vol. 28 (6): 572-582 [Abstract] ( 791 ) [HTML 1KB] [ PDF 259KB] ( 1355 )
 583 The Superiorities of Simultaneous Empirical Bayes Estimation for the Regression Coefficients and Error-Variance in Linear Model Chen Ling,Wei Laisheng When the hyperparameters of prior distribution are partly known in linear model, the simultaneous parametric empirical Bayes estimators (PEBE) of the regression coefficients and error variance are constructed. The superiority of PEBE over the least squares estimator (LSE) of regression coefficients is investigated in terms of the the mean square error matrix (MSEM) criterion, and the superiority of PEBE over LSE of the error variance is discussed under the the mean square error (MSE) criterion. Finally, when all hyperparameters are unknown, the PEBE of regression coefficients and error variance are reconstructed and the superiority of them over LSE under the MSE criterion are studied by simulation methods. 2012 Vol. 28 (6): 583-600 [Abstract] ( 979 ) [HTML 1KB] [ PDF 331KB] ( 1214 )
 601 Identifying the Causal Effects of Stochastic Interventions by Augmented Causal Networks Shan Na,Dong Xiaogang Suppose that the cause-effect relationships between variables can be described by a causal network. To identify the causal effect of a stochastic intervention, an augmented causal network for stochastic intervention is proposed in this paper. Then, we obtain two graphical criteria for identifying the causal effects of stochastic interventions from passive observations on observed variables only. When either of the two criteria is satisfied, a simple closed-form expression is provided for the causal effect of a stochastic intervention, which enables researchers to assess the causal effect with little effort. 2012 Vol. 28 (6): 601-613 [Abstract] ( 865 ) [HTML 1KB] [ PDF 199KB] ( 1101 )
 614 Variable Selection for Partially Linear Models via Adaptive LASSO Li Feng,Lu Yiqiang,Li Gaorong Partially linear model is a class of commonly used semiparametric models, this paper focus on variable selection and parameter estimation for partially linear models via adaptive LASSO method. Firstly, based on profile least squares and adaptive LASSO method, the adaptive LASSO estimator for partially linear models are constructed, and the selections of penalty parameter and bandwidth are discussed. Under some regular conditions, the consistency and asymptotic normality for the estimator are investigated, and it is proved that the adaptive LASSO estimator has the oracle properties. The proposed method can be easily implemented. Finally a Monte Carlo simulation study is conducted to assess the finite sample performance of the proposed variable selection procedure, results show the adaptive LASSO estimator behaves well. 2012 Vol. 28 (6): 614-624 [Abstract] ( 1564 ) [HTML 1KB] [ PDF 251KB] ( 3102 )
 625 Impact Assessment for Fuzzy Linear Regression Model Based on Case Deletion Zhang Aiwu Least squares method based on Euclidean distance and Lebesgue distance between fuzzy data is used to study parameter estimation of fuzzy linear regression model based on case deletion respectively. And the parameter estimations on two kinds of distance are compared. The input of the above model is real data and output is fuzzy data. The statistical diagnosis --- estimation standard error of regression equations is constructed to test highly influential point or outlier in observation data. At last through identifying highly influential point or outlier in actual data, it shows that the statistic constructed in this paper is effective. 2012 Vol. 28 (6): 625-636 [Abstract] ( 822 ) [HTML 1KB] [ PDF 223KB] ( 1100 )
 637 Some Properties of g-Covariance and g-Correlation Coefficient Hao Tao A new nonlinear covariance based on $\fn_jvn \100dpi \inline g$-expectation, $\fn_jvn \100dpi \inline g$-covariance, is introduced and some properties of $\fn_jvn \100dpi \inline g$-covariance including commutativity, homogeneity, additivity are studied. According to these results, the sufficient and necessary condition of $\fn_jvn \100dpi \inline g$-covariance satisfied homogeneity and additivity is obtained. That is $\fn_jvn \100dpi \inline g$, a linear function of $\fn_jvn \100dpi \inline z$. Correlation coefficient based on $\fn_jvn \100dpi \inline g$-expectation does not rang from -1 to 1 and it does not reflect the linear relationship between two random variables, either. 2012 Vol. 28 (6): 637-646 [Abstract] ( 1161 ) [HTML 1KB] [ PDF 232KB] ( 1252 )
 647 The Asymptotic Estimate of Absolute Ruin Probabilities in the Renewal Risk Model with Constant Force of Interest Wang Jingjing,Zhu Dongjing,Qian Wenying In this paper, absolute ruin problems for a kind of renewal risk model with constant interest force are studied. For certain situations of the claim distribution with heavy tail, consider the surplus of the arrival time, and discrete the surplus process, then use the method of renewal function and convolution, we present the asymptotic properties of absolute ruin probability when the initial surplus tends to infinity. 2012 Vol. 28 (6): 647-654 [Abstract] ( 881 ) [HTML 1KB] [ PDF 230KB] ( 1166 )
 655 A Reduced Model with Thinning-Dependence Structure Liang Xue,Wang Guojing The class of reduced form models is a very important class of credit risk models, and the modelling of the default dependence structure is essential in the reduced form models. This paper models dependent defaults under a thinning-dependent structure in the reduced form framework. In our tractable model, the joint survival probability for correlated defaults can be derived, and hence the CDS premium rates (with or without counterparty risk) are given in closed form. The numerical result shows that the thinning-dependent structure is effective to model the default dependence. 2012 Vol. 28 (6): 655-664 [Abstract] ( 850 ) [HTML 1KB] [ PDF 238KB] ( 1257 )
 665 The Properties and Applications of Invariable Function for Markov Chains in Random Environments Li Mingliang,Liu Zaiming In this paper, various concepts of recurrence and transience are introduced into the research field of Markov chains in random environments, and the concepts and properties of invariant function for Markov chains in random environments are investigated. By using those properties, we obtain a criterion for the state to be recurrent or transient. 2012 Vol. 28 (6): 665-672 [Abstract] ( 917 ) [HTML 1KB] [ PDF 172KB] ( 1301 )

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