Statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data

In this article, the statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data is discussed. The estimation of the parameters for Gompertz distribution is obtained using maximum likelihood method (MLE) and Bayesian method under three different loss functions. We also proved the existence and uniqueness of the MLE. The one-sample Bayesian prediction intervals are obtained. The work is done for different values of the parameters. We apply the Monto Carlo simulation to compare the proposed methods, also an example is discussed to construct the Prediction intervals.     

Bayesian expectile regression with asymmetric normal distribution

In this paper, we adopt the Bayesian approach to expectile regression employing a likelihood function that is based on an asymmetric normal distribution. We demonstrate that improper uniform priors for the unknown model parameters yield a proper joint posterior. Three simulated data sets were generated to evaluate the proposed method which show that Bayesian expectile regression performs well and has different characteristics comparing with Bayesian quantile regression. We also apply this approach into two real data analysis.     

Three-group ROC predictive analysis for ordinal outcomes

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning, and credit scoring. The receiver operating characteristic (ROC) surface is a useful tool to assess the ability of a diagnostic test to discriminate among three-ordered classes or groups. In this article, nonparametric predictive inference (NPI) for three-group ROC analysis for ordinal outcomes is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modeling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. This article also includes results on the volumes under the ROC surfaces and consideration of the choice of decision thresholds for the diagnosis. Two examples are provided to illustrate our method.     

Identification-robust moment-based tests for Markov switching in autoregressive models

ABSTRACT

This paper develops tests of the null hypothesis of linearity in the context of autoregressive models with Markov-switching means and variances. These tests are robust to the identification failures that plague conventional likelihood-based inference methods. The approach exploits the moments of normal mixtures implied by the regime-switching process and uses Monte Carlo test techniques to deal with the presence of an autoregressive component in the model specification. The proposed tests have very respectable power in comparison with the optimal tests for Markov-switching parameters of Carrasco et al. (2014 Carrasco, M., Hu, L., Ploberger, W. (2014). Optimal test for Markov switching parameters. Econometrica 82(2):765–784.[Crossref], [Web of Science ®] , [Google Scholar]), and they are also quite attractive owing to their computational simplicity. The new tests are illustrated with an empirical application to an autoregressive model of USA output growth.     

中国房地产税制:存在问题与改革设想

在现代市场经济条件下,房地产税制具有十分重要的功能。现阶段中国房地产税制存在房地产税收功能分散,房地产税种设置交叉重叠现象突出,计税依据不符合国际惯例,房地产保有环节税负偏轻和房地产税权分布结构不合理等问题。中国房地产税制改革已进入基础性制度建设阶段,必须按照"宽税基、简税种、低税率"的原则,实现房地产开发流转环节税收为主向房地产保有环节税收为主的房地产税制转型,去土地财政化,这就要适时开征房产税。开征房产税可以分两步走,近期对居民新购商品房超免税标准部分征收房产税,中长期覆盖到居民已购存量房地产。     

振兴东北老工业基地的金融支持

区域经济发展的差异与国家现行的统一的金融政策在制度安排上的不一致,构成了现行的金融政策制度与振兴东北老工业基地之间的基本矛盾。以金融结构论、金融深化论、金融约束论为代表的发展金融学,对制定振兴东北老工业基地的金融支持政策,具有重要的理论指导作用。振兴东北老工业基地金融支持的具体措施包括:发展风险投资事业;设立东北老工业基地振兴基金;组建东北振兴银行;化解银行不良资产。