nonparametric model 中文意思是什麼
nonparametric model
解釋
非參數模型- nonparametric : 非參數
- model : n 1 模型，雛型；原型；設計圖；模範；（畫家、雕刻家的）模特兒；樣板。2 典型，模範。3 （女服裝店僱...
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Nonparametric software reliability model concerned with censored data
一種考慮數據截尾的非參數軟體可靠性模型 -
Cumulative method in semiparametric regression model - nonparametric estimator base on wavelet smoothing
非參數估計基於小波光滑 -
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 -
Unlike the normal two stages estimate method ( the usual nonparametric weighted method combined with the least square estimate ), considering the characteristics of this model, this paper uses the least square estimate combining with the usual nonparametric weighted method and defines the estimators and n2 for the unknown parameter, the unkown fuction g ( ) and the unknown variance of errors 2
與通常採用的兩階段估計方法即非參數權函數法結合最小二乘法不同，考慮到此模型本身的特性，本文採用最小二乘法結合一般非參數權函數估計方法，定義了未知待估參數和未知函數g （ ? ）及誤差方差~ 2的估計量（ ? ） _ n ， （ ? ） _ n （ ? ）和（ -
In chapter, we study the nonparametric and linear model with weak sta - tionary linear model
在本文的第三章中，研究了誤差是弱平穩線性過程的線性模型與非參數回歸模型。 -
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。 -
A wavelet network model for nonparametric estimation and economic forecasting
非參數估計的小波網路經濟預測模型 -
Nonparametric multivariate regression model of urban daily water demand
城市日用水量預測的非參數模型 -
This paper studies the nonparametric estimates of general weight function of the nonparametric regression function with fixed design points, when the model error is martingale sequence, and we give the optimal convergence rate under some conditions
摘要當誤差為鞅差序列時，研究固定設計點列情形下非參數回歸函數一般權函數的非參數估計，並在一些基本條件下給出了估計的一致最優強收斂速度。 -
So many statistics scholars have studied it extensively and obtained many ideal results. semiparametric regression model yi ~ ( n ) = xi ~ ( n ) + g ( t ~ n _ i ) + _ i ~ ( n ), 1 i n, where g is an unknown function on a compact set a in r ~ p and is an unknown parameter, ( x _ 1 ~ ( n ), x _ 1 ~ ( n ) ) ~ t, ? ? x _ n ~ ( n ), t _ n ~ ( n ) ) ~ t are fixed design vectors and the radom er - rors _ i ~ ( n ) are assumed to be an l ~ q - mixingale sequences. fan [ 1 ] investigated nonparametric regression model
由於半參數回歸模型的優點是集中了主要部分（即參數分量部分）的信息，因而它比傳統的線性模型或非參數回歸模型有更強的解釋能力，不少統計學者對其進行了深入的研究，同其它回歸模型一樣，它的大樣本性質始終是人們關注的熱點。 -
Nonparametric model is widely used in the practical problems, the reason is that the form of the regression function in the nonparametric model is free, and the limits to the random variate ( x, y ) are fewer. in the past several decades, this model is studied carefully by the researchers of statistics, and many achievements are arrived in both theorial fields and in applicational fields
非參數回歸模型，由於其回歸函數的形式可以任意，而且對隨機變量（ x ， y ）的分佈限制較少，因而在實際中有著廣泛的應用背景。幾十年來，統計工作者對這一模型進行了深入細致的研究。無論在理論上還是應用上，都取得了許多優秀成果。 -
In this dissertation, the research trends for the problem have been introduced ; the ‘ dim ’ and ‘ point ’ has been strictly defined in mathematics from machine vision and human vision ; the ideal clutter suppression system based on clutter predication and the realization and evaluation of evaluation index has been studied, in succession the clutter suppression technologies have been researched. firstly, the classic nonparametric algorithm has been analyzed in detail and systematically, for it ’ s weakness that it cannot remove the non - stationary clutter ideally, kalman filter algorithm for clutter suppression in 2d image signal has been built. secondly, fast adaptive kalman filter is presented based on fast wide - sense stationary areas partition algorithm : limited combination and division algorithm based on quarti - tree algorithm, new taxis filter route algorithm which can break through the limitation of the necessity of pixel neighborhood of 2d filter and laplace data model with two parameters which is perfectly suitable for the residual image of kalman clutter suppression
首先分析了經典的非參數法，對於四種具有代表性的核，從前述的三個性能評價方面做了分析和對比，指出了其速度快的優點和對非平穩圖像適應性差的弱點，針對非參數法的弱點，重點研究了對非平穩圖像適應良好的卡爾曼雜波抑制技術:建立了非平穩圖像的類自回歸模型，在此基礎上建立了二維卡爾曼濾波基礎的兩個方程:狀態方程和測量方程;建立了非平穩圖像準平穩區域快速劃分演算法:基於四叉樹法的有限分裂合併演算法;二維空間的基於k排序的濾波路線演算法，突破了空域濾波路線上區域相鄰的限制;在這些研究的基礎上實現了快速卡爾曼估計，實驗驗證了該方法相對逐點卡爾曼估計可以提高運算速度三倍左右;雜波抑制結果表明傳統的高斯性檢驗並不適合卡爾曼估計后的殘余圖像，由此建立了殘余圖像的雙參數拉普拉斯模型，實驗表明其可以完好的吻合殘余圖像的概率密度曲線。 -
The basic idea of the estimate method is, firstly, based on the linear model yi = x ' i + ei, defining the least square estimator n of the linear model for the unkown parametric ; secondly, using the estimator n we " ve got to substitute for in the original semiparametric regression model yi = x ' i + g ( xi ) + ei and using the usual nonparametric weighted function method to define the estimator gn ( - ) for the unknown function g ( ) ; finally, defining the estimator 2 for the unknown variance of errors 2
其估計方法的基本思路是先基於線性模型y _ i = x _ i + e _ i ，定義未知待估參數的估計即此線性模型的最小二乘估計（ ? ） _ n ；然後將所得估計（ ? ） _ n代入原半參數回歸模型中，用一般的非參數權函數方法定義未知函數g （ ? ）的估計（ -
Simulation model of driving behavior based on the cubic spline nonparametric fitting regression
基於三次樣條非參數擬合的駕駛行為模擬模型 -
This paper is concerned with parametric component and nonparametric component estimators in a semiparametric regression model. this model is more flexible and explantory than traditional linear or nonparametric model
本篇論文主要討論關於半參數回歸模型的參數和非參數的估計問題，半參數回歸模型是近十幾年發展起來的一種統計模型。 -
To the nonparametric model, we still obtain the rth - mean and completely consistency which generalize and improve the results in [ 4 ] ; to the linear model, we obtain the rth - mean and completely consistency which is a new result
； k ）滿足較一般性的條件下，仍獲得了g 。 ）的r階平均相合性和一致平均相合性，推廣和改進了tran在文獻的結果，並在加上適當的條件，獲得g 。 -
This kind of model includes not only a parametric component but also a nonparametric component. so it has the advantages of the parametric regression model and the nonparametric regression model. it has the more implements and stronger explanations than the pure parametric or nonparametric regression model
這種模型既有參數分量，又含有非參數分量，兼顧了參數回歸模型和非參數回歸模型的優點，較單純的參數回歸模型或非參數回歸模型有更大的適應性，並具有更強的解釋能力。 -
In the light of the data of american treasury bill earning rate and interest rate swap, in combination of our country ' s data of treasury bill earning rate, the term structure of interest rate is simulated by using nonparametric support vector machine forecasting model, and on the basis of this, a systemic method of interest rate swap pricing is formulated by using support vector machine method to estimate fixed interest rate of swap
依據美國國庫券收益率和互換利率數據，結合我國國庫券收益率數據，採用非參數的支持向量機預測模型模擬出利率期限結構；在已知利率期限結構的基礎之上，採用支持向量機的方法模擬估計出利率互換的固定利率，從而構造出一種系統的利率互換定價方法。 -
In this paper, we discuss the estimate of regression function in nonparametric regression model based on exponential integral martingale difference
摘要本文研究了誤差項是鞅差序列，且滿足某種指數矩條件的非參數回歸函數的估計。
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