本文選題：廣義非線(xiàn)性回歸 + 缺失數(shù)據(jù)�。� 參考：《南京理工大學(xué)》2017年碩士論文

【摘要】：論文研究的是帶有缺失數(shù)據(jù)的廣義非線(xiàn)性模型基于經(jīng)驗(yàn)似然的統(tǒng)計(jì)診斷,對(duì)非線(xiàn)性模型進(jìn)行了推廣,首先利用經(jīng)驗(yàn)似然的方法來(lái)對(duì)參數(shù)進(jìn)行估計(jì),并構(gòu)造了參數(shù)的漸進(jìn)置信區(qū)間。當(dāng)響應(yīng)變量隨機(jī)缺失時(shí),取缺失概率分別為π(x)=0.5,0.8,樣本容量分別為n=20,50,100,每種情況重復(fù)模擬2000次,通過(guò)模擬,得出結(jié)論:經(jīng)驗(yàn)似然方法的覆蓋率與一般方法的覆蓋率相比都比較大;對(duì)于固定的缺失概率π,隨著樣本容量n增大,經(jīng)驗(yàn)似然方法與一般方法的平均區(qū)間長(zhǎng)度均變短,覆蓋率均增加。當(dāng)樣本容量n固定,缺失概率π越大,經(jīng)驗(yàn)似然方法與一般方法的覆蓋率越大,平均區(qū)間長(zhǎng)度越短,但是經(jīng)驗(yàn)似然方法比一般方法更加明顯的提高了覆蓋率。接著又對(duì)模型進(jìn)行統(tǒng)計(jì)診斷,介紹了如何檢測(cè)實(shí)際數(shù)據(jù)與既定模型之間可能存在的偏離,對(duì)模型進(jìn)行數(shù)據(jù)刪除度量和局部影響分析,并提出經(jīng)驗(yàn)似然距離、經(jīng)驗(yàn)Cook距離以及標(biāo)準(zhǔn)化殘差等診斷統(tǒng)計(jì)量。最后又結(jié)合實(shí)例進(jìn)行分析,選擇合適的模型,找出了數(shù)據(jù)中的強(qiáng)影響點(diǎn),驗(yàn)證了診斷統(tǒng)計(jì)量的有效性。
[Abstract]:In this paper, the generalized nonlinear model with missing data is studied based on the statistical diagnosis of empirical likelihood, and the nonlinear model is generalized. First, the parameters are estimated by the empirical likelihood method. The asymptotic confidence interval of the parameters is constructed. When the response variables are randomly missing, the probability of deletion is 0. 50.8, the sample size is nong 2050100, and the simulation is repeated 2000 times in each case. Through simulation, it is concluded that the coverage of the empirical likelihood method is larger than that of the general method. For the fixed loss probability 蟺, with the increase of sample size n, the average interval length of both the empirical likelihood method and the general method becomes shorter and the coverage rate increases. When the sample size n is fixed, the loss probability 蟺 is larger, the coverage of empirical likelihood method and general method is larger, and the average interval length is shorter, but the empirical likelihood method increases the coverage rate more obviously than the general method. Then it makes statistical diagnosis of the model, introduces how to detect the possible deviation between the actual data and the established model, measures data deletion and local impact analysis of the model, and puts forward the empirical likelihood distance. Empirical Cook distance and standardized residuals and other diagnostic statistics. Finally, an example is used to analyze and select the appropriate model to find out the strong influence points in the data, and verify the validity of the diagnostic statistics.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：O212.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 徐偉娟;林金官;;基于最大L_q似然估計(jì)的廣義非線(xiàn)性模型的統(tǒng)計(jì)診斷(英文)[J];Journal of Southeast University(English Edition);2013年01期

2 丁先文;徐亮;林金官;;非線(xiàn)性回歸模型的經(jīng)驗(yàn)似然診斷[J];應(yīng)用數(shù)學(xué)學(xué)報(bào);2012年04期

3 施紅星;;Poisson回歸模型的局部影響分析[J];楚雄師范學(xué)院學(xué)報(bào);2012年06期

4 謝書(shū)培;韓俊林;;Logistic回歸模型的統(tǒng)計(jì)診斷與實(shí)例分析[J];聊城大學(xué)學(xué)報(bào)(自然科學(xué)版);2011年01期

5 徐亮;丁先文;林金官;;基于經(jīng)驗(yàn)似然的部分線(xiàn)性模型的統(tǒng)計(jì)診斷[J];應(yīng)用概率統(tǒng)計(jì);2011年01期

6 郁文;鄭明;;缺失數(shù)據(jù)均值推斷的經(jīng)驗(yàn)似然方法[J];數(shù)學(xué)年刊A輯(中文版);2010年01期

7 梁怡;;缺失數(shù)據(jù)的插補(bǔ)調(diào)整方法[J];西安文理學(xué)院學(xué)報(bào)(自然科學(xué)版);2009年01期

8 張昕;;不完備信息系統(tǒng)下空缺數(shù)據(jù)處理方法的分析比較[J];海南師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2008年04期

9 周雁;;廣義線(xiàn)性模型的診斷與實(shí)例分析[J];四川大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年06期

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