Forecast mean squared error reductionin the VAR(1) process

When VAR models are used to predict future outcomes, the forecast error can be substantial. Through imposition of restrictions on the off-diagonal elements of the parameter matrix, however, the information in the process may be condensed to the marginal processes. In particular, if the cross-autocorrelations in the system are small and only a small sample is available, then such a restriction may reduce the forecast mean squared error considerably.

In this paper, we propose three different techniques to decide whether to use the restricted or unrestricted model, i.e. the full VAR(1) model or only marginal AR(1) models. In a Monte Carlo simulation study, all three proposed tests have been found to behave quite differently depending on the parameter setting. One of the proposed tests stands out, however, as the preferred one and is shown to outperform other estimators for a wide range of parameter settings.     

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 prediction of order statistics with fixed and random sample sizes based on k-record values from Pareto distribution

In this paper, the two-parameter Pareto distribution is considered and the problem of prediction of order statistics from a future sample and that of its geometric mean are discussed. The Bayesian approach is applied to construct predictors based on observed k-record values for the cases when the future sample size is fixed and when it is random. Several Bayesian prediction intervals are derived. Finally, the results of a simulation study and a numerical example are presented for illustrating all the inferential procedures developed here.     

Extended scaled prediction variance optimality for modified central composite design

Robust parameter designs (RPDs) enable the experimenter to discover how to modify the design of the product to minimize the effect due to variation from noise sources. The aim of this article is to show how this amount of work can be reduced under modified central composite design (MCCD). We propose a measure of extended scaled prediction variance (ESPV) for evaluation of RPDs on MCCD. Using these measures, we show that we can check the error or bias associated with estimating the model parameters and suggest the values of α recommended for MCCS under minimum ESPV.     

掺硼金刚石膜热敏电阻器的制备工艺及温度响应

介绍了一种帽状结构的掺硼金刚石膜热敏电阻器及其制备工艺。使用ＰＣＶＤ方法在Ｓｉ３Ｎ４或Ｓｉ基片上淀积掺硼金刚石膜，然后在金刚石膜上淀积Ｔｉ／Ａｕ薄膜以形成欧姆接触电极。结果获得了具有良好温度响应和欧姆接触的金刚石膜热敏电阻器。     

基于单片机的粮仓温度测控系统设计

介绍了一种基于AT89C51单片机的温度测控系统。使用AD590作为温度传感器对粮仓内温度进行监测,实时显示温度。系统对温度的控制合理、有效,具有调试方便、精度高和可靠性好等优点。     

除尘器区低温省煤器烟道数值模拟

为实现除尘器区低温省煤器的节能改造,基于FLUENT6.3软件,对除尘器区低温省煤器烟道的流场进行数值模拟研究。研究结果表明:除尘器前烟道内流场严重不均,转弯处有明显的高速区与漩涡区,局部速度高达32 m/s;加装低温省煤器后,两低温省煤器内流场不均,最大速度偏差系数达79.3%,严重影响低温省煤器的换热效果,同时会磨损、冲刷低温省煤器管路,危及低温省煤器的安全;除尘器入口处出现大面积的低速区域,导致进入除尘器后流场紊乱、除尘器电耗高、除尘效率低等现象,除尘器前烟道内整流消涡可以根治除尘器工作效率的问题。     

1998年狮子座流星暴的一些预测

1998年狮子座流星暴是本年度最重要的天象之一。而广东省处于观测的最有利位置,为了不错过这次十分难得的机会,本文叙述了狮子座流量暴的本质及其观测工作的意义,求出了该流星暴母体的部分轨道根数;对1998年狮子座流星暴作了一些预测;对观测方法提出了一些建议,本次预测虽用的是天文专业的方法,但为了使更多的观测员理解,本文尽可能使用最基础的知识。