弱平稳 meaning in Chinese
weakly stationary
Examples
- In chapter , we study the nonparametric and linear model with weak sta - tionary linear model
在本文的第三章中，研究了误差是弱平稳线性过程的线性模型与非参数回归模型。 - This dissertation deals with how to estimate parameters of a model of multivariable weak stable auto - regression equation on time series ( marked by ar ( p ) ) and formulizes properties of them
本文系统地研究了多元弱平稳序列自回归模型ar ( p )的参数估计方法及性状。 - This paper consists of two parts : in the first part , we will discuss the prob - lem of the pth - mean , complete consistency for the estimators of a nonparamet - ric and linear model with l ~ p - mixingale errors ; in the second part , we will dis - cuss the problem of the rth - mean 、 complete consistency for the estimators of themodels above with weak stationary linear process errors and the uniformly mean consistency . to the nonparametric model y _ ni = g ( x _ ni ) + _ ni , 1 i n , let g _ n ( x ) = w _ ni ( x , w _ n1 , … ? xnn ) y _ ni estimate the unknown function g ( x ) . to the linear model y _ i - x _ i1 1 + … ? + x _ iq ? _ q , we use lse _ nj to estimate the unknown parametric _ j
本篇论文主要是由两大部分内容构成：一是关于误差是l ~ p ?混合序列的线性回归模型参数的最小二乘估计与非参数回归模型未知函数的权函数估计的p ~ -阶平均相合性和完全收敛性问题；另一部分是关于误差是弱平稳线性过程的线性模型参数的最小二乘估计与非参数回归模型未知函数的权函数估计的r ?阶平均相合性和完全收敛性以及权函数估计的一致平均相合性问题。 - A kind of complete convergence of sums for negatively associated sequences of non - identically distributed random variables , in the second chapter , is obtained and the requirement of known results are weakened to the condition that absoluted moment - larger than zero - is finite . the strong convergence of negatively associated sequences of non - identically distributed random variables is discussed in the third chapter . in the fourth chapter , after extend the laws of the iterated logarithm of strong stationary case to weak stationary case , we obtain the strong convergence rate for negatively associated sequences of non - identically distributed random variables in linear models
其中第二章讨论了一类不同分布的na列的加权和的完全收敛性，我们把已有的结果对矩的要求放宽到了只要求大于0的绝对矩有限的情形；第三章讨论了不同分布的na列的加权和的强收敛性；第四章首先把文[ 10 ]的关于na的重对数律由强平稳的情形推广到了弱平稳不同分布的情形，然后得到了线性模型中不同分布的na误差列的收敛速度。 - A important result is the one - orde r expression of ar ( p ) yt = dyt - 1 + e , from paralleling a high - order differential equation transformation into a one - order differential equation system , the one - order expression exposes that the ar ( p ) is only a certain more - multivariable power series process and , if a process is described as an ar ( p ) , the sufficient and necessary condition is the spectrum norm a of the coefficient matrix d less than one . simplification of ar ( p ) not only brings about orthogonal f ( h ) but also provides global foretelling formula
作者用高阶微分方程化一阶微分方程组的方法，获得多元弱平稳序列p阶自回归模型的一步滑动平均表达式，证明了ar ( p )的是一个更高维的幂级数的线性过程，从而，说明了ar ( p )关于序列依概率成立的充要条件是：该模型更高维的幂级数的线性过程的表达式中系数矩阵d的谱范数1 。