本文選題：隨機(jī)效應(yīng)　切入點(diǎn)：固定效應(yīng)　出處：《北京化工大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：縱向數(shù)據(jù)是實(shí)踐分析中一種常見(jiàn)的數(shù)據(jù)類型,它既含有時(shí)間序列數(shù)據(jù)又包含橫截面數(shù)據(jù),從而可在研究客觀目標(biāo)的動(dòng)態(tài)行為時(shí)提供非常有用的信息。統(tǒng)計(jì)分析中針對(duì)縱向數(shù)據(jù)的研究模型和方法有很多,其中變系數(shù)部分線性模型因其具有較強(qiáng)的解釋能力和靈活性而在統(tǒng)計(jì)和經(jīng)濟(jì)等領(lǐng)域得到廣泛的應(yīng)用。實(shí)際生活中對(duì)于數(shù)據(jù)的采集可能存在各種測(cè)量誤差,因此基于縱向數(shù)據(jù)建立變系數(shù)部分線性EV模型具有很強(qiáng)的現(xiàn)實(shí)意義,并成為統(tǒng)計(jì)學(xué)界研究的重點(diǎn)課題之一。本文研究了縱向數(shù)據(jù)下變系數(shù)部分線性EV模型的參數(shù)估計(jì)和個(gè)體效應(yīng)的檢驗(yàn)問(wèn)題。首先在忽略測(cè)量誤差的情況下,通過(guò)最小二乘估計(jì)方法和局部線性估計(jì)方法,分別在隨機(jī)效應(yīng)模型和固定效應(yīng)模型下導(dǎo)出了參數(shù)和非參數(shù)部分的估計(jì)量。進(jìn)一步當(dāng)協(xié)變量帶有測(cè)量誤差時(shí),經(jīng)過(guò)糾偏處理得到修正后的估計(jì)量,并在大樣本下證明估計(jì)具有相合性和漸近正態(tài)性。為了識(shí)別個(gè)體效應(yīng)的類型,我們提出參數(shù)Hausman檢驗(yàn)統(tǒng)計(jì)量對(duì)模型個(gè)體效應(yīng)進(jìn)行檢驗(yàn)。我們分別在大樣本和小樣本下討論了參數(shù)Hausman檢驗(yàn)的應(yīng)用,首先從理論上證明了參數(shù)檢驗(yàn)統(tǒng)計(jì)量在大樣本下漸近服從卡方分布,并模擬結(jié)果顯示參數(shù)估計(jì)量的估計(jì)效果不錯(cuò)且在隨機(jī)效應(yīng)假設(shè)下檢驗(yàn)統(tǒng)計(jì)量近似服從卡方分布；而在小樣本下結(jié)合Bootstrap抽樣方法得到檢驗(yàn)的拒絕域,并通過(guò)模擬研究驗(yàn)證檢驗(yàn)統(tǒng)計(jì)量的檢驗(yàn)功效,數(shù)值模擬結(jié)果顯示基于Bootstrap抽樣的參數(shù)Hausman檢驗(yàn)在小樣本下具有很好的表現(xiàn)。
[Abstract]:Longitudinal data is a common data type in practical analysis. It contains both time series data and cross section data. This provides very useful information when studying the dynamic behavior of objective targets. There are many models and methods for longitudinal data in statistical analysis. Among them, partial linear models with variable coefficients have been widely used in statistical and economic fields because of their strong explanatory ability and flexibility. Therefore, it is of great practical significance to establish partial linear EV model with variable coefficients based on longitudinal data. In this paper, the parameter estimation and individual effect test of partial linear EV model with variable coefficients under longitudinal data are studied. By using the least square estimation method and the local linear estimation method, the estimators of the parametric and non-parametric parts are derived under the stochastic effect model and the fixed effect model, respectively. The modified estimator is obtained by rectifying the error, and the consistency and asymptotic normality of the estimator are proved under the large sample. In order to identify the type of individual effect, We propose a parameter Hausman test statistic to test the individual effects of the model. We discuss the application of parametric Hausman test in large and small samples, respectively. Firstly, it is proved theoretically that the parameter test statistics are asymptotically obedient to the chi-square distribution under large samples, and the simulation results show that the estimation effect of the parameter estimators is good and the test statistics are similar to the subordinate chi-square distributions under the assumption of random effects. Under the small sample and Bootstrap sampling method, the test rejection domain is obtained, and the effectiveness of test statistics is verified by simulation research. The numerical simulation results show that the parameter Hausman test based on Bootstrap sampling has a good performance in small samples.
【學(xué)位授予單位】：北京化工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：O212.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前7條

1 胡成盛;李志強(qiáng);王倩瑩;;變系數(shù)部分線性EV面板數(shù)據(jù)模型的效應(yīng)檢驗(yàn)[J];北京化工大學(xué)學(xué)報(bào)(自然科學(xué)版);2016年02期

2 王倩瑩;李志強(qiáng);胡成盛;;部分線性面板數(shù)據(jù)模型中個(gè)體效應(yīng)的Bootstrap Hausman檢驗(yàn)[J];北京化工大學(xué)學(xué)報(bào)(自然科學(xué)版);2016年01期

3 張征宇;朱平芳;;有測(cè)量誤差時(shí)空間自回歸模型的估計(jì)與檢驗(yàn)[J];統(tǒng)計(jì)研究;2010年04期

4 白仲林;史哲;;存在測(cè)量誤差的面板自回歸模型的工具變量估計(jì)[J];統(tǒng)計(jì)與信息論壇;2009年10期

5 ;Generalized Empirical Likelihood Inference in Semiparametric Regression Model for Longitudinal Data[J];Acta Mathematica Sinica(English Series);2008年12期

6 武大勇;劉林;;有測(cè)量誤差動(dòng)態(tài)面板數(shù)據(jù)模型的參數(shù)估計(jì)[J];安陽(yáng)師范學(xué)院學(xué)報(bào);2008年02期

7 秦國(guó)友;縱向數(shù)據(jù)線性回歸模型中最小二乘估計(jì)效率的比較[J];蘇州科技學(xué)院學(xué)報(bào);2005年03期

，

本文編號(hào)：1609426