回归估计

A kind of linear estimator is derived in linear regression model.

提出了线性模型中回归系数的一类线性估计。

In POT model, it used the technique of parameter estimator stability, making up for the limits of the currently popularly-used Mean Excess Function e, and the threshold quantitatively selected by Kurtosis Method has also been achieved, and solving the problem the illustration method couldn't be applied to.

特别是，在BMM模型中充分地考虑了子区间极值一般极限分布与极值序列极限分布之间的关系，测度了受子区间长度影响的极值VaR；在POT模型中运用参数估计量稳定性法弥补了目前普遍采用的样本平均超出量函数e法的不足，针对一些图解法无法适用的问题，实现了峰度法对阈值的定量选取，并对指数回归模型法、子样本自助法、序贯法等定量法进行了分析探讨。

Firstly an approximate linear model was obtained by confining the regression function in a functional space with finite dimension. Then the interval estimator was proposed by Fiducial inference.

首先将回归函数限制在一个有限维函数空间中，得到一个近似的线性模型，在此基础上，由Fiducial推断给出了误差方差的区间估计。

This paper describes the least one-power method of estimating the parameters in linear regression model of two variables,which is used in the solving method by fixed point, general solving method,two points method and simplex method.

论述了用最小一乘法估计两变数线性回归模型中的参数。计算方法为：通过定点的解法，一般解法，两点法和单纯形法。

An application of free energy framework on support vector regression machine parameters estimation is presented, and the corresponding formulas for selecting parameters and hyper parameters are derived to verify the feasibility and validity of this method.

应用自由能框架，对通常较难求解的贝叶斯支持向量回归机器的参数与超参数迸行估计，推导出相应的计算公式，并验证了该方法的可行性与有效性。

In nonparametric statistical theory, the nonparametric regression model that is with the given sample of observations are independent and identically distributed and the response .

在非参数统计理论中，对于给定的一组关于两变量和的非参数回归模型，其中已知，希望通过对的核估计得到更好的拟合模型。

This paper uses ridge estimation method to solve the potential ill-conditioned problem in semiparametric regression model.

针对半参数回归模型求解过程可能出现的法方程病态问题，提出了用岭估计原则改进半参数模型的求解。

In this paper, a multiple-regression-model-based missing values imputation algorithm is proposed.

提出了一种基于多元回归模型的缺失值估计算法。

The reliability data were collected by Langlie test, and then were processed to be order restricted with the isotonic regression.

该方法利用保序回归对Langlie法试验数据进行处理，给出参数的序约束估计。

Namely, the first, the beginning, end and length of growing season of every type of vegetation is estimated with threshold method and moving average method, and the beginning end and length of growing season of vegetation from 1982 to 1999 is fitted linearly, finally, linear trend of the beginning end and length of growing season of vegetation is analyzed. The second, phenological phase in different years and zones is estimated based on greatest changes of slope method and EOF analysis method, and the result monitored by the two methods is compared, as a result, trend of growing season change from 1982 to 1999 in different latitude zones is better acquired. The third, phenological phase of vegetation in different spatial location from 1982 to 1999 is fitted based on curve. Then, spatial difference rules of growing season of every year and average of multi-year is discussed in article. In the end, lag correlation and linear regress are used to study relation between phenological phase of different types of vegetation, different latitude zones, different spatial places and climate changes.

利用阈值法和滑动平均法逐年估测了每种植被类型的生长季的开始、结束日期及长度；对18年中植被生长季的开始、结束时间和长度进行一次线性拟合，分析了植被生长季的开始、结束日期和长度的线性变化趋势；基于最大变化斜率法和EOF分析法估计了不同年份、不同区域内植被生长季的开始、结束时间及其长度，并对这两种方法的监测结果作了比较，从而得到了较好的不同纬度区域1982～1999年植被生长季的变化趋势；基于曲线拟合了1982～1999年的不同空间位置的植被物候期，然后讨论了每年和多年平均的植被生长季的空间分异规律；最后利用时滞相关分析和线性回归研究了不同类型植被的物候期与气候变化的相互关系，不同纬度带的植被物候期与气候变化的相互关系，植被物候期与气候变化空间相互关系。

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。