随机回归模型的选择是回归分析理论中的重要问题之一。
Selecting a stochastic regression model is an important question in regression analysis theory.
本文在矩阵损失下研究了一般增长曲线模型中随机回归系数线性估计的可容许性。
We investigate the admissibility of the linear estimate of random regression coefficients under a matrix loss function in general growth curve models.
采用随机影响负二项回归模型，评估深管井的使用对儿童发生腹泻的影响。
The effect of deep tube well use on the incidence of childhood diarrhoea was assessed using a random effects negative binomial regression model.
西格玛黑带应能识别在各种可能原因的列表中，哪一个原因最合适解释在回归残差中出现的非随机分布。
The Six Sigma Black Belt should be able to identify which cause on a list of possible causes will most likely explain a non-random pattern in the regression residuals.
本文利用时间序列谱分析和卡尔曼滤波的方法讨论了两个随机过程，主要是自回归滑动平均(ARMA)过程，的叠加问题。
Using the methods of time series spectral analysis and Kalman filter, this article discussed the additive problems of two stochastic processes, mainly Auto Regression Moving Average (ARMA) processes.
目的探讨白色念珠菌磷脂酶活性与随机扩增多态性DNA（RAPD）电泳条带之间的关系，构建多元回归模型。
Objective To research the relationship between the phospholipase activities and the random amplified polymorphic DNA(RAPD) bands of Candida albicans, and establish the regression model.
对一般线性回归模型中有关参数估计分布的模拟问题，给出一种随机加权逼近的再构造方法。
A reconstructing method for random weighting approximations is proposed in approach to the distributions of the parameter estimates in general linear regression model.
但是，近年来均值回归理论对随机漫步理论提出了挑战。
But, in recent years, Average Value Return Theory gave a challenge to the Random Walk Theory.
在影响因素分析的过程中，通过将效率影响因素引入随机前沿模型进行因素分析，避免了一般使用两阶段因素回归法可能造成的偏差。
In analyzing the factors affecting efficiency, we puts the factors into the stochastic frontier model, which avoids the deviation caused by using two-period factors regression method.
针对一个线性回归模型的系统矩阵存在的随机扰动情况，提出一种基于均匀设计的稳健参数估计算法。
A robust parameters estimation algorithm is proposed in this paper, which is based on uniform design for a linear regression model in the case of its coefficient matrix with random disturbance.
主要考虑了同方差型的半参数线性回归模型中参数的随机加权最小二乘估计（RWLSE）。
The randomly weighted least square estimator (RWLSE) for the parametric component in semi-parametric regression models was mainly discussed.
本文介绍的插补方法有：演绎估计，均值插补，随机插补，回归插补和多重插补。
This paper introduces several imputation methods: those methods include: Deductive imputation, Mean value imputation, Randomized imputation Regression method and Multiple imputation.
本文讨论了回归独立性与随机独立性之间的关系，得到了两者等价的几个充分必要条件。
The relation between regressive independence and random independence is discussed, and several necessary and sufficient conditions are presented.
基于自回归滑动平均模型(ARMA)的方法，实现了不同车速和路面条件下的随机振动信号的实验室再现。
The reconstruction of vehicle random vibration signal under different vehicle speed and road conditions is realized in laboratory, based on an auto regressive moving average (ARMA) time series model.
采用随机区组试验设计，通过方差分析、多重比较及回归分析，研究不同配方基质性质与油松容器苗生长及生理特性的关系和对苗木生长的影响。
Using randomized block experiment design and variance analysis, multiple comparisons and regression analysis methods; the effects of the container-growing seedling were systematically analyzed.
作者应用随机模型中多元线性回归的方法建立了沈阳地区地下水位动态变化模型。
A model showing dynamic change of groundwater level for Shenyang area is set up, using the method of multivariate linear regression in random model.
最常使用的五个模型是石油期货价格、回归结构模型、时间序列分析、贝叶斯自回归模型和动态随机一般均衡图。
The five models used most often are oil futures prices, regression-based structural models, time-series analysis, Bayesian autoregressive models and dynamic stochastic general equilibrium graphs.
利用催化剂线源扩散模式确定人工增雨作业后的目标区，并采用非随机活动对比区和目标区分层历史回归的方法估算作业效果。
The regression analysis method of non stochastic process and movable control over the target area was used to assess seeding effect. The target area was determinated by diffusion equation.
首先，叙述用回归分析与随机时间序列技术的组合方法来处理大坝的监测数据。
First presented is a method of regression analysis combined with random time series technique for analysis of monitoring data of DAMS.
采用回归法分析了矿体厚度与古地貌之间的关系，据统计研究，矿体厚度属随机变量。
Correlation factors between them are analyzed via statistic regression, where thickness of ore formation is regarded as a random variation.
回归相关分析作为研究随机现象的重要数学方法，在水资源不确定性分析中具有广泛应用。
As one of the mathematical ways to study the random phenomena, regression analysis is the important tool to study the uncertainty of basin water resources.
基于粘弹性随机有限元法（VSFEM）和多项式回归模型，分析了固体火箭发动机药柱结构的随机参数灵敏度。
Stochastic parameter sensitivity of SRM grain structure was analyzed based on viscoelastic stochastic finite element method(VSFEM) and polynomial regression model.
提出了一种用随机加权的方法去逼近线性回归模型中M-估计的渐近分布。
Rao and Zhao (1992) developed the random weighting method for M-estimates in regression models.
该文在分析了时间序列模型的自回归系数对结构单元刚度灵敏度的基础上，提出了一种采用随机载荷作用下结构的时域响应数据进行损伤识别的新方法。
A new method is developed for identifying structural damages at the element level by using time-domain response data at a few points caused by random loadings.
同时考虑样地的随机效应、观测数据的时间序列相关性及不同初植密度的混合模型模拟精度比传统的非线性回归方法模拟精度高。
The precision of mixed model considering plot random effects, time series error autocorrelation and different plantation density at one time is better than that of ordinary regression analysis method.
该文针对风速随机变化的特性，在风速统计特性研究的基础上，用自回归滑动平均(ARMA)方法建立了具有一定功率谱密度特性的风速模型。
This paper deals with stochastic characteristic of the wind speed, and gives an auto-regressive moving-average (ARMA) model for wind speed subjected to particular power spectral density.
提出了随机系数泛函自回归模型，得到了几何遍历性的充分条件。
In this paper, a random coefficient functional autoregressive model is proposed and the sufficient condition of the geometric ergodicity is obtained.
应用线性回归分析和移动平均理论，对按时间次序排列的单一数据序列，给出了一种线性移动自回归预测模型，并对原始数据受不确定因素影响而产生的随机振荡，给出了合理的控制区间和运行通道。
The theory of linear regression and the theory of moving average are applied to analyse single data in time series, the model of a linear moving self regression forecast are given out.
回归分析是一种非常有用且灵活的分析方法，它是在一组试验或观测数据的基础上，寻找被随机性掩盖了的变量之间的依存关系。
Regression analysis is a very useful and flexible analysis method. It is based on a group of tested or observed data to find the relationship between variables that are random covered.
回归分析是一种非常有用且灵活的分析方法，它是在一组试验或观测数据的基础上，寻找被随机性掩盖了的变量之间的依存关系。
Regression analysis is a very useful and flexible analysis method. It is based on a group of tested or observed data to find the relationship between variables that are random covered.
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