A Spatial-temporal Model for Temperature with Seasonal Variance

We propose a spatial-temporal stochastic model for daily average surface temperature data. First, we build a model for a single spatial location, independently on the spatial information. The model includes trend, seasonality, and mean reversion, together with a seasonally dependent variance of the residuals. The spatial dependency is modelled by a Gaussian random field. Empirical fitting to data collected in 16 measurement stations in Lithuania over more than 40 years shows that our model captures the seasonality in the autocorrelation of the squared residuals, a property of temperature data already observed by other authors. We demonstrate through examples that our spatial-temporal model is applicable for prediction and classification.     

干线战术通信网的抗毁模型研究

介绍了抗毁通信网分析与设计的原理和方法、针对干线战术通信网中节点移动会导致网络拓扑结构发生变化的特点,提出了动态网络拓扑设计模型和衡量干线战术通信网的抗毁性能的数学模型—随机图模型和齐次随机图模型、计算机模拟结果验证了随机图模型和齐次随机图模型的正确性.     

半平面上有限级随机Dirichlet级数的增长性

证明了右半平面上有限级随机Dirichlet级数的增长性几乎必然与其在每条水平直线上的增长性相同。     

两种m重-四角链图的优美性

刘春峰等证明了A型m重—四角链图、B型m重—四角链图的k—优美性及序列性。文章给出了另一种优美标号(也是k—优美标号),且在此标号下证得了这两种m重—四角链图是交错图,且具有奇优美性及平衡性。     

The number of records within a random interval of the current record value

LetX ₁,X ₂, … be a sequence of i.i.d. random variables with some continuous distribution functionF. LetX(n) be then-th record value associated with this sequence and μ _n ⁻ , μ _n ⁺ be the variables that count the number of record values belonging to the random intervals(f−(X(n)), X(n)), (X(n), f+(X(n))), wheref−, f+ are two continuous functions satisfyingf−(x)<x, f+(x)>x. Properties of μ _n ⁻ , μ _n ⁺ are studied in the present paper. Some statistical applications connected with these variables are also provided.     

Consistent deconvolution in density estimation

Suppose we have n observations from X = Y + Z, where Z is a noise component with known distribution, and Y has an unknown density f. When the characteristic function of Z is nonzero almost everywhere, we show that it is possible to construct a density estimate f_n such that for all f, Iim_n| |=0.     

Complete consistency for the estimator of nonparametric regression models based on extended negatively dependent errors

In this paper, we provide some exponential inequalities for extended negatively dependent (END) random variables. By using these exponential inequalities and the truncated method, we investigate the complete consistency for the estimator of nonparametric regression model based on END errors. As an application, the complete consistency for the nearest neighbour estimator is obtained.     

A multilevel model with autoregressive components for the analysis of tribal art prices

In this paper, we introduce a multilevel model specification with time-series components for the analysis of prices of artworks sold at auctions. Since auction data do not constitute a panel or a time series but are composed of repeated cross-sections, they require a specification with items at the first level nested in time-points. Our approach combines the flexibility of mixed effect models together with the predicting performance of time series as it allows to model the time dynamics directly. Model estimation is obtained by means of maximum likelihood through the expectation–maximization algorithm. The model is motivated by the analysis of the first database ethnic artworks sold in the most important auctions worldwide. The results show that the proposed specification improves considerably over classical proposals both in terms of fit and prediction.     

Estimating school effectiveness with student growth percentile and gain score models

Measuring school effectiveness using student test scores is controversial and some methods used for this can be inaccurate in some situations. The validity of two statistical models – the Student Growth Percentile (SGP) model and a multilevel gain score model – are evaluated. The SGP model conditions on previous test scores thereby unblocking a backdoor path between true school/teacher effectiveness and student test scores. When the product of the coefficients that make up this unblocked backdoor path is positive, the SGP estimates can be inaccurate. The accuracy of the multilevel gain score model was not associated with the product of this backdoor path. The gain score model appears promising in these situations where the SGP and other covariate adjusted models perform poorly.     

Estimation and simulation of conditional hazard function in the quasi-associated framework when the observations are linked via a functional single-index structure

We consider the estimation of the conditional hazard function of a scalar response variable Y given a Hilbertian random variable X when the observations are linked via a single-index structure in the quasi-associated framework. We establish the pointwise almost complete convergence and the uniform almost complete convergence (with the rate) of the estimate of this model. A simulation is given to illustrate the good behavior in the practice of our methodology.