Bayesian Inference and Forecasting in Dynamic Neural Networks with Fully Markov Switching ARCH Noises

We deal with one-layer feed-forward neural network for the Bayesian analysis of nonlinear time series. Noises are modeled nonlinearly and nonnormally, by means of ARCH models whose parameters are all dependent on a hidden Markov chain. Parameter estimation is performed by sampling from the posterior distribution via Evolutionary Monte Carlo algorithm, in which two new crossover operators have been introduced. Unknown parameters of the model also include the missing values which can occur within the observed series, so, considering future values as missing, it is also possible to compute point and interval multi-step-ahead predictions.     

Maximum Likelihood Estimation for Multinomial‐Poisson Models: A Generalization of Birch's Numerical Invariance Results

Abstract. This study gives a generalization of Birch's log‐linear model numerical invariance result. The generalization is given in the form of a sufficient condition for numerical invariance that is simple to verify in practice and is applicable for a much broader class of models than log‐linear models. Unlike Birch's log‐linear result, the generalization herein does not rely on any relationship between sufficient statistics and maximum likelihood estimates. Indeed the generalization does not rely on the existence of a reduced set of sufficient statistics. Instead, the concept of homogeneity takes centre stage. Several examples illustrate the utility of non‐log‐linear models, the invariance (and non‐invariance) of fitted values, and the invariance (and non‐invariance) of certain approximating distributions.     

社会资本投资与中小企业融资约束--基于中国中小板上市公司的实证分析

通过将社会资本投资因素引入欧拉投资模型,探析了社会资本投资对中小企业融资约束的动态影响,并以2008—2012年深交所中小板上市公司为研究样本,实证检验社会资本投资对中小企业融资约束的缓解作用。结果发现：中国中小企业投资支出与内部经营活动现金流显著正相关,普遍面临融资约束问题;而娱乐支出和获得直接政治关联是中小企业构建关系社会资本的有效措施,能在很大程度上缓解企业的融资约束。     

A Bootstrap Approach for Testing Marginal Independence Between Two Categorical Variables When Subjects Have Repeated Responses

To assess independence in two-way contingency tables, the Pearson chi-square test or Fisher’s exact test are typically used. These tests assume that each subject contributes at most one count to only one table cell (e.g., sex versus blood type). In other situations, each subject may have more than one count contributing to the table and these counts may occur in different cells of the table. One may wish to test independence, adjusting for the within-subject correlation. We provide a simple nonparametric bootstrap approach and assess its performance through simulation studies. The method is illustrated on subjects with multiple mental health presentations to Emergency Departments.     

A Partially Linear Model Using a Gaussian Process Prior

A partially linear model is a semiparametric regression model that consists of parametric and nonparametric regression components in an additive form. In this article, we propose a partially linear model using a Gaussian process regression approach and consider statistical inference of the proposed model. Based on the proposed model, the estimation procedure is described by posterior distributions of the unknown parameters and model comparisons between parametric representation and semi- and nonparametric representation are explored. Empirical analysis of the proposed model is performed with synthetic data and real data applications.     

基于流动性偏好的上市公司现金持有行为研究

以流动性偏好理论为基础,通过理论模型推导出不同融资约束的公司会依据其现金流波动性进行有差异的现金持有行为决策;以2001～2006年间4 285个公司年数据为样本,实证检验并分析了中国上市公司融资约束、现金流波动性和现金持有量之间的相互关系.结果表明:在中国资本市场,融资约束公司的现金流波动性高于非融资约束公司,而现金持有量却低于非融资约束公司;前者现金持有量与现金流波动性显著正相关,而后者无显著相关性.     

资源环境约束下的新疆工业发展方式研究

新疆工业化进程面临巨大的资源和环境约束,新疆脆弱的生态环境和有限的资源供给已经难以支撑粗放的工业发展方式。随着资源环境约束的日益显现,新疆必须通过技术创新、转变工业发展方式、发展循环经济来缓解资源环境压力,走新型工业化道路,实现资源环境约束下的新疆工业可持续发展。     

工具理性的拯救——中国特色社会主义市场经济下的道德约束重建

由于我国市场经济的发展一开始就融入到国际化的分工之中,因此不能像西方经典市场经济一样,自发地衍生出与之相匹配的道德约束,这也使得我国社会趋向"囚徒困境"。因此,只能依靠外在的有意识的道德约束建设来解决这个问题。而这种道德约束建设要通过信任的建立来降低利他行为作出的成本,从而建立起利他行为生发体系,进而达成道德约束的建设。     

Rank covariance matrix estimation of a partially known covariance matrix

Classical multivariate methods are often based on the sample covariance matrix, which is very sensitive to outlying observations. One alternative to the covariance matrix is the affine equivariant rank covariance matrix (RCM) that has been studied in Visuri et al. [2003. Affine equivariant multivariate rank methods. J. Statist. Plann. Inference 114, 161–185]. In this article we assume that the covariance matrix is partially known and study how to estimate the corresponding RCM. We use the properties that the RCM is affine equivariant and that the RCM is proportional to the inverse of the regular covariance matrix, and hence reduce the problem of estimating the original RCM to estimating marginal rank covariance matrices. This is a great computational advantage when the dimension of the original data vector is large.     

A marginalized diffusion model for estimating age at first lower endoscopy use from current status data

Summary.  We propose an approach for estimating the age at first lower endoscopy examination from current status data that were collected via two series of cross-sectional surveys. To model the national probability of ever having a lower endoscopy examination, we incorporate birth cohort effects into a mixed influence diffusion model. We link a state-specific model to the national level diffusion model by using a marginalized modelling approach. In future research, results from our model will be used as microsimulation model inputs to estimate the contribution of endoscopy examinations to observed changes in colorectal cancer incidence and mortality.