In this paper, empirical Euclidean likelihood ratio statistics are constructed for parametric in a nonlinear model. And prove strong consistency and asymptotic normality of the estimation.
本文构造了非线性模型中参数的经验欧氏似然比统计量，并证明了该似然估计的强相合性和渐近正态性。
To the different problems in practice, three main aspects are involved in this paper: the estimation of motion vector field, the parametric tracking model of lv and probability tracking model of lv.
针对实际应用的不同侧重点，本文核心内容包括三方面：LV的运动矢量场估计、LV参数化运动跟踪模型和LV的概率跟踪模型。
Based on EM approach of right dock, it gives out parametric estimation of accelerated life testing in linear model.
基于右截尾的EM算法，给出了恒加试验线性模型的参数估计，并结合加速方程得到了产品的寿命估计。
The problem of the parametric estimation on a convolutional model is discussed.
讨论褶积模型参数估计问题。
With bispectrum analysis, an ar model parametric bispectrum estimation is presented for radar target echoes.
本文利用双谱分析方法，提出用非高斯ar模型对雷达目标回波信号进行参数化双谱估计。
The paper applied the information diffusion model of non-parametric estimation to project the level of productivity risks for cereals, rice, corn and wheat at major grain-producing area.
本文采用非参数估计的信息扩散模型测算了我国粮食主产区水稻、玉米、小麦和棉花产量损失风险水平。
The disadvantages were that this method was based on assumptions on the model: point estimation based on parametric assumption and some properties of error components.
但是这种方法也有不足之处，就在于它对模型有一些弱的假定点估计依赖于误差因子与模型参数的假定，密度估计依赖于误差因子特征函数的假定。
The disadvantages were that this method was based on assumptions on the model: point estimation based on parametric assumption and some properties of error components.
但是这种方法也有不足之处，就在于它对模型有一些弱的假定点估计依赖于误差因子与模型参数的假定，密度估计依赖于误差因子特征函数的假定。
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