發(fā)布時間：2018-07-31 05:53

【摘要】：分段檢驗理論主要包括有序樣本聚類與分段假設(shè)檢驗兩部分.分段檢驗理論在企業(yè)營銷效應(yīng),提升質(zhì)量有效性等領(lǐng)域有著廣泛的應(yīng)用,準(zhǔn)確評價相關(guān)措施或政策的有效性,對政策或措施的管理具有重要的意義,因而對分段檢驗理論及其應(yīng)用的研究就顯得尤為重要.在有序樣本聚類方面,首先,提出利用組內(nèi)離差平方和與組間離差平方和構(gòu)建F統(tǒng)計量建立優(yōu)化模型實現(xiàn)有序樣本聚類,并將其應(yīng)用于成都市和北京市環(huán)境空氣指數(shù)歷史數(shù)據(jù)分類.當(dāng)樣本容量較大時,基于F統(tǒng)計量的優(yōu)化模型必須存儲每一類的F值,最優(yōu)分割法都必須存儲每一類對應(yīng)直徑,使得計算效率差.而模擬退火算法具有良好的全局搜索能力,將模擬退火算法與最優(yōu)分割法目標(biāo)函數(shù)相結(jié)合可避免存儲類的直徑,提高算法計算效率,因此提出基于模擬退火算法的有序樣本聚類.最后利用成都環(huán)境空氣指數(shù)歷史數(shù)據(jù)進(jìn)行實證分析,取得較好的分類結(jié)果.在分段假設(shè)檢驗方面,根據(jù)樣本是否存在相關(guān)性分為兩類.當(dāng)分段樣本相互獨(dú)立時,提出運(yùn)用經(jīng)典的假設(shè)檢驗理論進(jìn)行均值與方差的參數(shù)檢驗,并將經(jīng)典假設(shè)檢驗理論與基于F統(tǒng)計量的優(yōu)化模型有序樣本聚類結(jié)合評價成都市環(huán)境空氣治理效應(yīng).當(dāng)分段樣本存在短期自相關(guān)時,結(jié)合平穩(wěn)時間序列性質(zhì),對正態(tài)假設(shè)下均值與方差參數(shù)檢驗進(jìn)行修正,并將分段檢驗中樣本均值與樣本方差的方差推廣到伽馬分布族.最后將分段檢驗理論與基于F統(tǒng)計量的優(yōu)化模型有序樣本聚類結(jié)合,實現(xiàn)北京市政府環(huán)境空氣治理效應(yīng)評價。
[Abstract]:The segmentation test theory mainly includes two parts: ordered sample clustering and segmental hypothesis test. Piecewise test theory has been widely used in the fields of enterprise marketing effect, improving quality and effectiveness. It is of great significance to accurately evaluate the effectiveness of relevant measures or policies for the management of policies or measures. Therefore, it is very important to study the theory of subsection test and its application. In the aspect of ordered sample clustering, first of all, an optimization model based on intra-group deviation square sum and inter-group deviation square sum is proposed to realize ordered sample clustering. It is applied to the classification of historical data of ambient air index in Chengdu and Beijing. When the sample size is large, the optimization model based on F statistics must store the F value of each class, and the optimal partition method must store the corresponding diameter of each class, which makes the calculation efficiency poor. The simulated annealing algorithm has a good global search ability. Combining the simulated annealing algorithm with the objective function of the optimal segmentation method can avoid the diameter of the storage class and improve the computational efficiency of the algorithm. Therefore, an ordered sample clustering based on simulated annealing algorithm is proposed. Finally, using the historical data of Chengdu Ambient Air Index, a good classification result is obtained. In segmented hypothesis testing, there are two categories according to the correlation of samples. When the piecewise samples are independent of each other, the classical hypothesis test theory is proposed to test the mean and variance parameters. The classical hypothesis test theory and the ordered sample clustering based on F statistics are combined to evaluate the effect of ambient air control in Chengdu. When there is a short-term autocorrelation in segmented samples, combining with the properties of stationary time series, the mean and variance parameter test under normal assumption is modified, and the variance of sample mean and sample variance is extended to the gamma distribution family. Finally, the piecewise test theory is combined with the ordered sample clustering of the optimization model based on F statistics to evaluate the environmental air control effect of Beijing government.
【學(xué)位授予單位】：四川師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：O212.1

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