Slashed generalized Rayleigh distribution

We introduce a new family of distributions suitable for fitting positive data sets with high kurtosis which is called the Slashed Generalized Rayleigh Distribution. This distribution arises as the quotient of two independent random variables, one being a generalized Rayleigh distribution in the numerator and the other a power of the uniform distribution in the denominator. We present properties and carry out estimation of the model parameters by moment and maximum likelihood (ML) methods. Finally, we conduct a small simulation study to evaluate the performance of ML estimators and analyze real data sets to illustrate the usefulness of the new model.     

A new generalization of the Weibull-geometric distribution with bathtub failure rate

In this paper, the researchers attempt to introduce a new generalization of the Weibull-geometric distribution. The failure rate function of the new model is found to be increasing, decreasing, upside-down bathtub, and bathtub-shaped. The researchers obtained the new model by compounding Weibull distribution and discrete generalized exponential distribution of a second type, which is a generalization of the geometric distribution. The new introduced model contains some previously known lifetime distributions as well as a new one. Some basic distributional properties and moments of the new model are discussed. Estimation of the parameters is illustrated and the model with two known real data sets is examined.     

Parameter estimation of the censored δ-shock model on uniform interval

The censored δ-shock model is a special kind of shock model and it has very important research values in the reliability theory. In this paper, we discuss the parameter estimation of the censored δ-shock model when the inter-arrival times between two successive shocks follows uniform distribution on [a, b]. With the maximum likelihood estimation, we obtain the parameter estimator and expectation of estimator and lifetime of the model. By numerical simulation, we get the empirical result on the estimator of δ and the relationship between δ and other parameters.     

The exponentiated reduced Kies distribution: Properties and applications

Here we consider an exponentiated version of the reduced Kies distribution and discuss some of its properties. The parameters of the distribution are estimated by the method of maximum likelihood and illustrated with the help of certain real-life data sets. Asymptotic behavior of the maximum likelihood estimators of the parameters of the distribution is also studied by using certain simulated data sets.     

Parameter estimation for multivariate diffusion processes with the time inhomogeneously positive semidefinite diffusion matrix

Statistical inference for the diffusion coefficients of multivariate diffusion processes has been well established in recent years; however, it is not the case for the drift coefficients. Furthermore, most existing estimation methods for the drift coefficients are proposed under the assumption that the diffusion matrix is positive definite and time homogeneous. In this article, we put forward two estimation approaches for estimating the drift coefficients of the multivariate diffusion models with the time inhomogeneously positive semidefinite diffusion matrix. They are maximum likelihood estimation methods based on both the martingale representation theorem and conditional characteristic functions and the generalized method of moments based on conditional characteristic functions, respectively. Consistency and asymptotic normality of the generalized method of moments estimation are also proved in this article. Simulation results demonstrate that these methods work well.     

An Adaptive Functional Autoregressive Forecast Model to Predict Electricity Price Curves

We propose an adaptive functional autoregressive (AFAR) forecast model to predict electricity price curves. With time-varying operators, the AFAR model can be safely used in both stationary and nonstationary situations. A closed-form maximum likelihood (ML) estimator is derived under stationarity. The result is further extended for nonstationarity, where the time-dependent operators are adaptively estimated under local homogeneity. We provide theoretical results of the ML estimator and the adaptive estimator. Simulation study illustrates nice finite sample performance of the AFAR modeling. The AFAR model also exhibits a superior accuracy in the forecast exercise of the California electricity daily price curves compared to several alternatives.     

新闻舆论引导与公正价值

公正价值作为政治价值范畴与社会价值范畴的交叉内容,构成新闻舆论引导的具体内涵之一。为避免一种公正价值主张的舆论对其他的公正价值产生抵牾,新闻从业者对公正价值观的丰富内涵应有准确把握与完整解读,善于以新闻事件为载体,理性倡导、型塑"适度的爱"与"最低限度的爱"、"获益条件与机会均等"、"所得待遇合乎其所享有权利"、"得其应得"与"先天条件最少者受惠"的公正价值舆论。     

学前儿童性别教育的研究现状及其启示

学前儿童性别教育的有关研究表明,社会上还存在着根深蒂固的性别歧视和性别偏见,身处特定环境中的学前教育教师以及图画书、教学媒体等仍然带有较强的性别歧视和性别偏见等性别刻板印记。为此,国家需要在学前儿童性别教育研究的基础上重视学前教育阶段的性别平等教育,制定相关的政策,建立性别教育的终身教育体系,构建教师性别平等教育的培训网络平台,以现代性别教育理念为指导,基于对儿童生理差异的尊重,设计出适合学前儿童身心发展特点的性别教育课程,全面有效地实施性别平等教育。     

缺失数据时两个对数正态分布的估计和检验

讨论了部分缺失数据两对敷正态分布的参数估计和关于总体相同的似然比检验.证明了估计的强相合性和渐近正态性,给出了似然比检验统计量的极限分布,并讨论基于精确分布的检验问题.