回归估计

In autoregression models, when the parameter from GED is known, adaptive rejection sampling method is used to estimate parameters; when the parameter from GED is unknown, we have to decide a range, also use the same method to give a reasonable estimate of the parameters.

在自回归模型中，GED分布的参数已知的情况下，基于似然函数的形式用拒绝抽样方法估计自回归系数；GED分布的参数未知时，我们给定参数的范围，用拒绝抽样方法寻找自回归系数合理的估计值。

In the fifth chapter, we propose the conditional generalized ridge-type estimator of regression coefficient in restricted linear regression model, and prove that it is superior to the restricted best linear unbiased estimator in terms of mean squares error and mean squares error matrix, we also give the choice of parameters matrix K.

第五章给出了约束线性回归模型中回归系数的条件广义岭估计，讨论了它的优良性，证明了它在均方误差及均方误差矩阵下都优于约束最小二乘估计，并给出了参数矩阵K的选择。

We apply the kernel methods of regression functions and conditional density functions to obtain a series of as the estimators of . Then using Monte Carlo Analysis method , we can get the optimal choice of the unknown parametric that is . Examples illustrate the models and will show this estimation is effective.

应用回归函数核估计和条件密度函数的核估计方法估计未知量，将得到的一组估计值用Monte Carlo Analysis方法处理便得到最优的，并通过算例模拟讨论以上估计方法的优劣。

Secondly, by the P-L estimation of survivor function, this paper proposed the regression models of polynomial cumulative hazard function distribution models, respectively in the case of complete date and random right censoring date; meanwhile generalized least squares estimations of unknown parameters were proposed respectively using two steps algorithm and principal component analysis algorithm.

与已有的关于多项式危险函数模型的研究成果相比，首先本文在统计模型的构造上充分考虑了累积危险函数乘积限估计量的非独立性，给出了协方差矩阵的估计；其次在模型检验方面，本文利用非参数回归分析方法，充分利用了数据本身的信息，减少了对回归关系假定的主观因素，因而分析结果更为可靠。

The simulation results also find that the Quasi-Aitken weighted least squares estimator has a smaller asymptotic variance than least squares estimator.

研究结果显示机率加权最小平方法与Quasi-Aitken机率加权最小平方法的回归参数估计式皆具有不偏性，其中Quasi-Aitken机率加权最小平方法的回归参数估计式的变异最小。

Topics covered include: density estimation incorporating such topics as kernel density estimates, nearest neighbor estimates, variable kernel methods, orthogonal series estimates, maximum penalized likelihood estimates

包括：密度估计（如：核密度估计，最近邻估计，可变核方法，正交序列估计，最大补偿似然估计法，带宽选择），非参数回归(如：核方法，样条方法，补偿似然估计，带宽选择，广义可加模型，)和bootstrapping方法。

Topics covered include: density estimation (incorporating such topics as kernel density estimates, nearest neighbor estimates, variable kernel methods, orthogonal series estimates, maximum penalized likelihood estimates, bandwidth choice), nonparametric regression (incorporating kernel methods, spline methods, penalized likelihood, bandwidth choice, generalized additive models), and bootstrapping.

非参数建模专题：非参数建模专题：基于计算机的非参数统计方法论。包括：密度估计(如：核密度估计，最近邻估计，可变核方法，正交序列估计，最大补偿似然估计法，带宽选择)非参数回归(如：，核方法，样条方法，补偿似然估计，带宽选择，广义可加模型，)和 bootstrapping 方法。

In this paper, we study the problems of the kernel regression estimator with spherical data, the estimators of multivariate densit...

本文主要研究了球面数据回归函数核估计以及多维密度函数估计和多维回归函数估计问题。

Second,a new estimator called generalized rootpower estimator of regression coefficients in growth curve model is obtained.For the newestimator,its superiority over the LS estimator and the root power estimator,and its admissibilityare proved.Two methods,two kinds of arithmetic of choosing the generalized root powerparameters are introduced.A demonstrative practical example is provided.

对增长曲线模型中的回归系数矩阵提出了一种新的估计——广义根方估计，并证明了通过广义根方偏参数的适当选取可使得该估计在均方误差和均方误差矩阵的意义下优于已有的最小二乘估计估计和根方估计；及证明了广义根方估计是可容许估计；还给出了选取广义根方偏参数的两种方法、算法和应用实例。

Multiple linear regression is the simplest way to build the relationship between the several explanatory variables and response variable. However, MLR often causes the estimated regression coefficients unstable or even unaccessible when the number of explanatory variables is more than that of objects. Especially, the explanatory variables are highly intercorrelated which called multi-collinear data. Therefore, many methods have been developed to analyze multi-collinear data, such as variable selection methods, ridge regression, principal components regression and partial least squares regression.

当要同时建立多个解释变数与反应变数间的关系时，最简单的方式是以复回归来处理，但是当解释变数数目远多於样本数，或者变数之间具有高度相关性时，会使得回归系数的估计变得不稳定甚至无法求得，这样的资料又称为共线性资料，在面临这样的资料时可以利用变数选取的方式降低资料组的维度，或者以脊回归、主成分回归及净最小平方回归等方法来灭种共线性的干扰。

On the other hand, the more important thing is because the urban housing is a kind of heterogeneity products.

另一方面，更重要的是由于城市住房是一种异质性产品。

Climate histogram is the fall that collects place measure calm value, cent serves as cross axle for a few equal interval, the area that the frequency that the value appears according to place is accumulated and becomes will be determined inside each interval, discharge the graph that rise with post, also be called histogram.

气候直方图是将所收集的降水量测定值，分为几个相等的区间作为横轴，并将各区间内所测定值依所出现的次数累积而成的面积，用柱子排起来的图形，也叫做柱状图。