發(fā)布時(shí)間：2019-01-27 22:15

【摘要】：連續(xù)性抽樣調(diào)查由于能夠描述目標(biāo)總體隨時(shí)間的動(dòng)態(tài)變化過(guò)程,吸引了越來(lái)越多國(guó)內(nèi)外學(xué)者的關(guān)注。國(guó)外連續(xù)性抽樣的研究已經(jīng)十分成熟,在已知的輪換模式下,建立合適的模型,使得模型能較好地描述數(shù)據(jù)的真實(shí)生成過(guò)程,從而得到精度更高的目標(biāo)估計(jì)量。文章建立一般輪換模式r~m_1~r~(m- 1)_2下的時(shí)間序列模型,然后以6~3~6~2模式為例,利用狀態(tài)空間模型和卡爾曼濾波,給出已有信息下的最優(yōu)估計(jì),有效減少抽樣誤差,提高樣本的估計(jì)精度。
[Abstract]:Continuous sampling survey has attracted more and more scholars' attention because of its ability to describe the dynamic process of target population over time. The research of continuous sampling abroad has been very mature. Under the known rotation mode, a suitable model is established, which can better describe the real process of data generation and obtain a more accurate target estimation. In this paper, the time series model of the general rotation model rnm-1 _ 2 is established. Then, taking the 6 ~ 3 ~ (-1) 2 model as an example, using the state space model and Kalman filter, the optimal estimation under the available information is given, which can effectively reduce the sampling error. Improve the estimation accuracy of the sample.
【作者單位】： 暨南大學(xué)經(jīng)濟(jì)學(xué)院;
【基金】：全國(guó)統(tǒng)計(jì)科學(xué)研究計(jì)劃項(xiàng)目(2012LY014) 霍英東教育基金會(huì)項(xiàng)目(141096) 廣東省優(yōu)秀博士學(xué)位論文資助項(xiàng)目(sybzzxm201120)
【分類號(hào)】：F224

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本文編號(hào)：2416752