相合性 的英文怎麼說
中文拼音 [xiānggěxìng]
相合性
英文
congruence-
The continuity and unigueness of the solution for the simultaneous equations of a class of gaussian diffusion process and analysis of consistency
隨機擴散過程方程組解的連續惟一及相合性分析Sequence and large sample quality are posed. in our country or allien there are many experts who discusses some quanlity of na variable in great. for example, in documentation 6, there is a discussion about the consistency of density kernel estimation and many results have been g ained, but the density estimation f ( x ) is limited to the arrange of x [ a, 6 ] which limits the arrange of application. thus in this passage we call off this limitation and further discuss the density kernel estimation under na sample. consequently the counterpart results have been gained and the condition of result has been weaked. in the same time we discuss the density kernel estimation under pa sample and the counterpart result has been gained
序列密度函數估計及其大樣本性質的研究課題。國內外許多專家對na變量的各種性質進行了大量的討論,其中文獻[ 6 ]曾對na樣本下密度核估計的相合性進行了討論,並取得了一些結果,但該文將密度估計f ( x )限制在x [ a , b ]中進行討論,這局限了應用范圍。因此本文在取消這種限制條件下對na樣本的密度核估計進行了進一步的討論,得出了相應的結果,並使結論的條件得到弱化;同時對pa樣本下的密度估計也進行了相應的討論,取得了相應的結果。On the other hand, they play an important role in the theories of esfimation for regression function. in this paper, we mainly get the large sample properties for partitioning estiona - tion and modified its estimation. for example, we proved their asymptolic normaity under nuture conditions by means of mortingle theory ; we also get their strong consistency for regression function under censored samples ; and finaly we genearzed the result to dependence sample and have strong consistency for the modified partitioning estimation of regression function
因此本論文研究了回歸函數基於分割估計及改良基於分割估計的大樣本性質,利用鞅的有關理論,在比較自然的條件下,證明了其漸近正態性;首次構造了截尾樣本的回歸函數基於分割估計及改良基於分割估計,並證明其強相合性;同時把有關結果推廣到相依樣本下(如混合) ,獲得了改良基於分割估計的強相合性及收斂速度。By taking repetitive observations in this paper, parametric estimators are obtained respectively in a simple structural ev linear model and a linear structural ev model with vector explanatory variables
本文利用重復抽樣的方法,分別給出了簡單線性結構型ev模型和一般線性結構型ev模型中的參數估計,並討論了估計的強相合性與漸近正態性。This paper also points out the consistency that can be generalized more than one dimension. so, we achieve the large sample property - consistency of this class of model on the fixed design. in this paper, for fixed design points xi ; under the assumption that the unknown function g is continuous function and the moment of random error exists and is finity, we discuss and show that the estimators n, gn and n2 for, g and 2 have strong consistency, p th - mean consistency for more general nonparametric weighted fuction
本論文在x ;是固定設計的情況下,假定未知函數9 ( ? )連續,對非參數權函數的條件更為一般和基本,並對隨機誤差e ;的矩的要求有限,討論並證明了在這些條件下, p ; g ( ? )的估計量札lin ( ? )及誤差方差a 』的估計量枯相合性和叭三2 )階平均相合性Asymptotic distribution ; consistency ; extreme - value index
漸近分佈相合性極值指數It is proposed that a new estimator of the extreme - value index when it is negative that is similar in form to the pickands estimator. its consistency and asymptotic distribution is established
提出一類極值指數為負時的相似於pickand s型的新的極值指數估計量,並建立它的相合性及漸近分佈。The limit distributions of estimators and likelihood ratio test are given, the strong consistency of estimators is also proved
證明估計的強相合性和漸近正態性,給出似然比檢驗統計量的極限分佈,並討論基於精確分佈的檢驗問題。By using rank statistic and order statistic, we obtain the asymptotically strongly consistent estimator of it, the hypothesis test and interval estimation are also discussed
利用秩統計量和次序統計量,獲得了變點的一種估計,不僅論證了點估計的強相合性,而且討論了假設檢驗和區間估計。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
本篇論文主要是由兩大部分內容構成:一是關于誤差是l ~ p ?混合序列的線性回歸模型參數的最小二乘估計與非參數回歸模型未知函數的權函數估計的p ~ -階平均相合性和完全收斂性問題;另一部分是關于誤差是弱平穩線性過程的線性模型參數的最小二乘估計與非參數回歸模型未知函數的權函數估計的r ?階平均相合性和完全收斂性以及權函數估計的一致平均相合性問題。In this paper, the limit theory is discussed and the main problems are solved as followed : 1. we will obtain asymptotic normality and consistency of mle for agarch model introduced by wu shuosi and fang zhaoben ( 2000 ). 2
對于吳碩思和方兆本( 2000 )提出的非對稱廣義自回歸條件異方差新模型,證明了它的極大似然估計( mle )的漸近正態性和相合性。This paper studies mainly the theories of the semi - parametric regression model : ( 1 ) under proper conditions, using random weighted way to the estimator of the error density f ( x ) of the semi - parametric regression model, this paper proved the strong and weak consistent and the asymptotic unbiased property of the weighted kernel estimation fn1 ( x ) of the f ( x )
本文對半參數回歸模型:主要做了以下三個方面的理論研究: ( 1 )將隨機加權法應用到半參數回歸模型的誤差密度f ( x )的估計當中去,在適當的條件下,證明了誤差密度的加權核估計( ? ) _ ( n1 ) ( x )的強相合性、弱相合性及漸近無偏性。The definition of the maximum likelihood estimator with the prior information ( pmle ) is given in this paper, and the consistency and asymptotic normality of pmle are proved
摘要定義了有先驗信息的極大似然估計,它能夠充分利用參數的先驗信息,還具有正規條件下的相合性和漸近正態性。At first, we prove the complete convergence of triangular arrays. then, we give the complete convergence of associated random variables. at last, the almost sure convergence and complete convergence of - mixing random variables " order statistics are given
樣本及m -相依樣本三角組列的完全收斂性;接著研究相伴隨機變量序列的完全收斂性;最後,還給出了混合隨機變量次序統計量的強相合性及完全收斂性。Strong consistency and asymptotic normality of maximum likelihood estimates
廣義線性回歸極大似然估計的強相合性Strong consistency in semiparametric regression model for contaminated data
污染數據半參數回歸模型中估計的相合性Consistency of the density kernel estimator for negatively and positively associated samples
樣本下密度核估計的相合性Strong consistency for estimators of a class semi - parametric reliability regression model
一類半參數可靠性回歸模型估計的強相合性Strong consistency of the nearest neighbor estimates of low dimensional component in additive models
可加模型中低維分量近鄰估計的強相合性Weak consistency of quasi - maximum likelihood estimates in multivariate generalized linear models
多維廣義線性模型擬極大似然估計的弱相合性分享友人