本文選題：部分線性變系數(shù)EV模型 + 調(diào)整加權最小二乘估計�。� 參考：《蘭州理工大學》2017年碩士論文

【摘要】：部分線性變系數(shù)模型是近年來提出的一個具有很強實際應用性的模型.該模型形式包含了很多子模型,例如參數(shù)、非參數(shù)以及半?yún)?shù)模型都可以看做為部分線性變系數(shù)模型的特例,所以其不但具有線性模型形式簡單,易于觀察的優(yōu)點、非參數(shù)模型穩(wěn)健的特征,還能夠動態(tài)的表達協(xié)變量與相應變量之間的相互關系.通常在建立回歸模型時,我們認為所得到的觀測數(shù)據(jù)都是完整的,準確的,且誤差項彼此相互獨立并不考慮數(shù)據(jù)測量誤差,或者缺失響應變量.但是在實際生產(chǎn)過程中,沒有測量誤差或者缺失響應變量的數(shù)據(jù),通常很難得到,或者需要付出極大成本去提高精度.而在實際生產(chǎn)過程中,這都是不現(xiàn)實的.所以當研究回歸模型時需要考慮到這些外部因素對模型的影響,然后再對模型的參數(shù)進行估計.第一章,主要介紹了本文所研究問題的背景、部分線性變系數(shù)EV模型的研究發(fā)展、現(xiàn)狀以及本文研究所需的一些理論知識.第二章,考慮模型在帶有測量誤差及約束條件下情形下的回歸情況.運用調(diào)整最小二乘估計和Lagrange乘數(shù)法估計未知參數(shù)和系數(shù)函數(shù),在一定條件下證明參數(shù)、非參數(shù)函數(shù)估計的相合性,并模擬實驗結果.第三章,研究了響應變量缺失下,參數(shù)具有線性約束且參數(shù)部分和非參數(shù)部分都帶有測量誤差的部分線性變系數(shù)模型的估計問題,利用最小二乘法和局部糾偏方法給出模型中參數(shù)和系數(shù)函數(shù)的估計,在一定的條件下證明了它們的漸近性質(zhì).
[Abstract]:Partial linear variable coefficient model is a model with strong practical application proposed in recent years. The model form contains many submodels, such as parametric, nonparametric and semi-parametric models, which can be regarded as special cases of partial linear variable coefficient models, so it not only has the advantages of simple form of linear model, but also easy to observe. The robust features of the nonparametric model can also dynamically express the relationship between the covariable and the corresponding variable. When we build the regression model, we think that the observed data are complete and accurate, and the error terms are independent of each other without considering the measurement error or the missing response variables. However, in the actual production process, the data without measurement errors or missing response variables are usually difficult to obtain, or need to pay a great deal of cost to improve the accuracy. In the actual production process, this is unrealistic. Therefore, when studying the regression model, we should consider the influence of these external factors on the model, and then estimate the parameters of the model. In the first chapter, we introduce the background of the problem, the research development of partial linear variable coefficient EV model, the present situation and some theoretical knowledge needed in this paper. In chapter 2, the regression of the model with measurement error and constraint is considered. By using the method of adjusted least square and Lagrange multiplier to estimate the unknown parameter and coefficient function, the consistency of parameter and nonparametric function estimation is proved under certain conditions, and the experimental results are simulated. In chapter 3, we study the estimation of partial linear variable coefficient model with linear constraints and measurement errors in both parametric and nonparametric parts under the absence of response variables. The estimation of the parameter and coefficient function in the model is given by using the least square method and the local correction method. Their asymptotic properties are proved under certain conditions.
【學位授予單位】：蘭州理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O212.1

【參考文獻】

相關期刊論文 前10條

1 李曉妍;劉瓊蓀;;缺失數(shù)據(jù)下帶約束條件的部分線性變系數(shù)EV模型的估計[J];西南師范大學學報(自然科學版);2014年11期

2 歐陽光;;變系數(shù)多維線性結構關系EV模型參數(shù)的加權M估計[J];湘南學院學報;2011年05期

3 馮三營;牛惠芳;;部分線性變系數(shù)EV模型估計的漸近正態(tài)性[J];河南科技大學學報(自然科學版);2011年02期

4 蒙家富;張日權;呂士欽;;誤差相關的半變系數(shù)模型的估計[J];應用概率統(tǒng)計;2010年05期

5 周麗;周道軍;;自適應變系數(shù)EV模型中系數(shù)參數(shù)的估計[J];湖南文理學院學報(自然科學版);2010年03期

6 周麗;;一類新型變系數(shù)EV模型中參數(shù)β的估計[J];長沙大學學報;2010年05期

7 魏傳華;;因變量缺失下部分線性變系數(shù)變量含誤差模型的估計[J];數(shù)學物理學報;2010年04期

8 李澤華;吳小臘;劉萬榮;;變系數(shù)EV模型系數(shù)參數(shù)核估計的改進估計[J];重慶師范大學學報(自然科學版);2010年01期

9 李澤華;劉萬榮;吳小臘;;變系數(shù)EV模型基于核估計的誤差方差估計[J];系統(tǒng)科學與數(shù)學;2009年03期

10 羅羨華;戴家佳;楊振海;;半?yún)?shù)變系數(shù)部分線性回歸模型的漸近性質(zhì)[J];北京工業(yè)大學學報;2007年06期

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