The maximum likelihood estimators in a multivariate normal distribution with AR(1) covariance structure for monotone data

The maximum likelihood estimators are uniquely obtained in a multivariate normal distribution with AR(1) covariance structure for monotone data. The maximum likelihood estimator of mean is unbiased.     

Seasonal Space–Time Models for Climate Systems

A class of seasonal space–time models for general lattice systems is proposed. Covariance properties of spatial first-order models are studied. Estimation approaches in time series analysis are adopted and forecasting techniques using the seasonal space–time models are discussed. The models are applied to 516 consecutive fields of monthly averaged 500 mb geopotential heights over a 10 × 10 lattice in the extra-tropical northern hemisphere for the purpose of understanding the underlying statistical structure. It is found that space–time models with instantaneous spatial component give the best fit compared to other models in terms of maximizing the conditional likelihood function. The models are potentially useful for assessing the consistency of outputs from laboratory-based numerical models with field observations. Forecasting ability of the seasonal space–time models is also investigated. This revised version was published online in June 2006 with corrections to the Cover Date.     

Calibrated Estimators of the Population Covariance

We introduce some calibrated estimators of a finite-population covariance. The estimators are defined by using different calibration equations and different loss functions. The estimators derived are compared by simulation. The study is supported by the Nordplus Neighbour program of the Nordic Council of Ministers.     

Separability of Mixed States of the Quantum Network of Three Nodes

This article discusses the complete separability and partial separability of the mixed states of quantumnetwork of three nodes by means of the criterion of entanglement in terms of the covariance correlation tensor in quantumnetwork theory.     

Two Level Systems Driven by a Stochastic Perturbation

Here we consider a two level system driven by an external harmonic field whose amplitude is perturbed by a white noise term. In the limit of small splitting, dynamical localization, i.e. coherent destruction of tunneling, is proved for times of the order of 1/ε, where ε is the two-level splitting. The same type of localization is proved if the driving field is simply the white noise.     

同步增长模型多元差估计量

在一些定期进行的多指标抽样调查中 ,调查指标的现期值与上期值之间的关系往往可以用同步增长模型描述 .本文利用两期指标之间的相关性构造了以上期指标为辅助指标的多元差估计量 ,讨论了多元差估计量的统计性质 ,证明在迹准则下多元差估计量优于多元简单估计量 .     

Efficient stochastic model for the point kinetics equations

A new stochastic model for the point kinetics equations with I-delayed neutron precursor groups is presented. In this stochastic model, the point kinetics equations are separated into three terms: prompt neutrons, delayed neutrons and external neutrons source. The matrix form of the efficient stochastic model is solved by a semi-analytical method. The semi-analytical method is based on the exponential function of the coefficient matrix. The eigenvalues of the coefficient matrix and Gaussian elimination are used to calculate this exponential function. The mean and standard deviation of neutron and precursor populations of the efficient stochastic model with step, ramp, and sinusoidal reactivities are computed. The results of the efficient stochastic model are compared with the results of Allen's stochastic model for the point kinetics equations. This comparison confirms that the efficient stochastic model is an accurate model compared with the deterministic point kinetics equations. This stochastic model is efficient to study the natural behavior of neutron and precursor populations in the nuclear reactor dynamics.     

Using indirect covariance spectra to identify artifact responses in unsymmetrical indirect covariance calculated spectra

Several groups of authors have reported studies in the areas of indirect and unsymmetrical indirect covariance NMR processing methods. Efforts have recently focused on the use of unsymmetrical indirect covariance processing methods to combine various discrete two-dimensional NMR spectra to afford the equivalent of the much less sensitive hyphenated 2D NMR experiments, for example indirect covariance (icv)-heteronuclear single quantum coherence (HSQC)-COSY and icv-HSQC-nuclear Overhauser effect spectroscopy (NOESY). Alternatively, unsymmetrical indirect covariance processing methods can be used to combine multiple heteronuclear 2D spectra to afford icv-13C-15N HSQC-HMBC correlation spectra. We now report the use of responses contained in indirect covariance processed HSQC spectra as a means for the identification of artifacts in both indirect covariance and unsymmetrical indirect covariance processed 2D NMR spectra.     

Multistep correlations via covariance processing of COSY/GCOSY spectra: opportunities and artifacts

Long-range homonuclear coupling pathways can be observed in COSY or GCOSY spectra by the acquisition of spectra with larger numbers of increments of the evolution period, t(1), than would normally be used. Alternatively, covariance processing of COSY-type spectra acquired with modest numbers of t(1) increments, allows the observation of multistage correlations. In this work results obtained from covariance-processed GCOSY spectra are fully analyzed and compared to normally processed COSY and 80 ms TOCSY spectra. Multistage or 'RCOSY-type' correlations are observed when remote protons both exhibit correlations to the same coupling partner e.g. A --> B and B --> C gives rise to an A --> C correlation. In the strict sense, RCOSY-type responses are artifacts albeit providing useful information. Nonbeneficial artifact correlations are observed when protons couple to other protons that overlap or partially overlap. The origin of artifact responses is also analyzed.     

Residual water suppression by indirect covariance NMR

Residual water solvent signals in 2D NMR experiments adversely affect appearance and subsequent analysis of spectra. A method for water suppression that is based on indirect covariance processing is described. It produces a symmetric spectrum with a water signal that is substantially decreased or completely absent. The method, which can be combined with other water suppression schemes, is demonstrated for 2D TOCSY, NOESY, and ROESY spectra of the protein, ubiquitin in aqueous solution.