【摘要】：在人口的遷徙和流動(dòng)中產(chǎn)生了大量的歷史數(shù)據(jù)，，如何準(zhǔn)確高效的利用這些數(shù)據(jù)得出具有政策導(dǎo)向意義的研究結(jié)果尤為重要。有理論表明人口的變動(dòng)在相鄰或者相近的地域之間有較為明顯的相關(guān)性，但在以往的研究中多是單純從時(shí)間維度上考慮人口結(jié)構(gòu)的變動(dòng)預(yù)測(cè)未來(lái)的走勢(shì)或是僅僅對(duì)人口的研究在空間統(tǒng)計(jì)的范疇內(nèi)進(jìn)行分析。本文綜合考慮空間和時(shí)間的依賴性，針對(duì)兩類時(shí)空數(shù)據(jù)：連續(xù)數(shù)據(jù)與格數(shù)據(jù)，分別借助空間殘差模型和克里格地理統(tǒng)計(jì)模型兩個(gè)研究方法進(jìn)行研究。 在理論方面，本文主要做了如下工作:對(duì)時(shí)空數(shù)據(jù)的類型介紹，時(shí)空數(shù)據(jù)建模的假設(shè)與前提，時(shí)空模型的形式，參數(shù)估計(jì)基本思想和極大似然的迭代方法，采用的似然比檢驗(yàn)以及預(yù)測(cè)方法。同時(shí)也簡(jiǎn)要討論了時(shí)空數(shù)據(jù)模型在實(shí)際中的應(yīng)用；在應(yīng)用層面借用以上的方法，通過(guò)R軟件編程實(shí)現(xiàn)了整個(gè)計(jì)算過(guò)程。在實(shí)證部分中，先對(duì)數(shù)據(jù)進(jìn)行描述性分析，初步了解其空間和時(shí)間維度的分布特點(diǎn)。同時(shí)做了統(tǒng)計(jì)解釋并根據(jù)數(shù)據(jù)的一階差分特征判定它是適用于空間殘差模型的，接下來(lái)進(jìn)行模型擬合和檢驗(yàn)發(fā)現(xiàn)其空間和時(shí)間依賴系數(shù)都顯著，為人口分布的空間依賴?yán)碚撎峁┝藬?shù)理方面的佐證，并對(duì)其進(jìn)行實(shí)際意義的解釋。而后對(duì)兩種模型的擬合結(jié)果做出了預(yù)測(cè)精度和計(jì)算效率的對(duì)比和評(píng)價(jià)，發(fā)現(xiàn)針對(duì)此問(wèn)題，時(shí)空克里格方法在預(yù)測(cè)精度上優(yōu)于空間誤差模型。以上研究?jī)?nèi)容為時(shí)空數(shù)據(jù)模型的分析提供數(shù)理方面的分析思路。 本文在進(jìn)行實(shí)證分析時(shí)采用的數(shù)據(jù)是瑞典的人口數(shù)據(jù)。因?yàn)槠淇臻g分辨率高，以教區(qū)為地理單位，比省市地區(qū)的數(shù)據(jù)精度要高，有助于在時(shí)空分析中得出準(zhǔn)確的結(jié)論，并且在時(shí)間維度上具有完整性和分割一致性。而國(guó)內(nèi)的人口數(shù)據(jù)主要通過(guò)人口普查得到的省市縣的數(shù)據(jù)，在數(shù)據(jù)的可獲得性和空間分辨率上有局限，并且在時(shí)空數(shù)據(jù)模型使用之前，需要對(duì)其進(jìn)行空間化的處理，考慮到工作量和時(shí)間成本因素，因而本文直接選取了直接可用來(lái)分析的瑞典人口時(shí)空數(shù)據(jù)。但只要數(shù)據(jù)質(zhì)量夠高，或者數(shù)據(jù)空間化的預(yù)處理已經(jīng)完成，在遇到時(shí)空數(shù)據(jù)模型問(wèn)題時(shí)，本文的研究思路是值得借鑒和參考的。
[Abstract]:A large number of historical data have been produced in the migration and flow of population. How to use these data accurately and efficiently to obtain policy-oriented research results is particularly important. There are theories that there is a clear correlation between population changes in adjacent or close regions, However, in the previous studies, it is only from the time dimension to consider the change of population structure to predict the future trend, or only to analyze the population research in the field of spatial statistics. In this paper, considering the dependence of space and time, two kinds of spatiotemporal data, continuous data and lattice data, are studied with the help of spatial residuals model and Kriging geographic statistical model, respectively. In theory, this paper mainly introduces the types of spatiotemporal data, the assumptions and premises of spatio-temporal data modeling, the form of spatio-temporal model, the basic idea of parameter estimation and the maximum likelihood iterative method. The likelihood ratio test and prediction method are used. At the same time, the application of spatio-temporal data model in practice is briefly discussed, and the whole calculation process is realized by using the above methods in the application level. In the empirical part, firstly, the data are analyzed descriptive, and the spatial and temporal distribution characteristics of the spatial and temporal dimensions are preliminarily understood. At the same time, the statistical explanation is made and the first order difference characteristic of the data is determined to be suitable for the spatial residual model. Then, the model fitting and testing are carried out and found that the spatial and time dependent coefficients are significant. It provides mathematical evidence for spatial dependence theory of population distribution and explains its practical significance. Then the prediction accuracy and computational efficiency of the two models are compared and evaluated. It is found that the spatial-temporal Kriging method is superior to the spatial error model in prediction accuracy. The above research content provides the mathematical analysis thought for the time-space data model analysis. The data used in this paper are Swedish population data. Because of its high spatial resolution, the parish is a geographical unit, which is more accurate than the data of provinces and cities, which is helpful to draw an accurate conclusion in time and space analysis, and has integrity and segmentation consistency in time dimension. However, the data of provinces, cities and counties, which are mainly obtained from the population census, are limited in terms of data availability and spatial resolution, and they need to be spatially processed before the use of spatio-temporal data models. Considering the factors of workload and time cost, this paper directly selects the space-time data of Swedish population which can be directly used to analyze. However, as long as the data quality is high enough, or the preprocessing of data spatialization has been completed, the research idea of this paper is worthy of reference and reference when we encounter the problem of spatiotemporal data model.
【學(xué)位授予單位】：首都經(jīng)濟(jì)貿(mào)易大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：C921

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 張林;牟子平;;地質(zhì)統(tǒng)計(jì)學(xué)在水環(huán)境研究中的應(yīng)用[J];環(huán)境科學(xué)與管理;2011年01期

2 肖斌,潘懋,趙鵬大,侯景儒;時(shí)空多元指示克立格法的理論研究[J];北京大學(xué)學(xué)報(bào)(自然科學(xué)版);2001年01期

3 姜曉軼;周云軒;;從空間到時(shí)間——時(shí)空數(shù)據(jù)模型研究[J];吉林大學(xué)學(xué)報(bào)(地球科學(xué)版);2006年03期

4 曾懷恩;黃聲享;;基于Kriging方法的空間數(shù)據(jù)插值研究[J];測(cè)繪工程;2007年05期

5 李功權(quán);曹代勇;;在GIS系統(tǒng)中整合地質(zhì)統(tǒng)計(jì)學(xué)的方法探討[J];測(cè)繪與空間地理信息;2006年02期

6 張小紅;程世來(lái);許曉東;;基于Kriging統(tǒng)計(jì)的GPS高程擬合方法研究[J];大地測(cè)量與地球動(dòng)力學(xué);2007年02期

7 呂安民,李成名,林宗堅(jiān),史文中;中國(guó)省級(jí)人口增長(zhǎng)率及其空間關(guān)聯(lián)分析[J];地理學(xué)報(bào);2002年02期

8 劉盛和;鄧羽;胡章;;中國(guó)流動(dòng)人口地域類型的劃分方法及空間分布特征[J];地理學(xué)報(bào);2010年10期

9 葉宇;劉高煥;馮險(xiǎn)峰;;人口數(shù)據(jù)空間化表達(dá)與應(yīng)用[J];地球信息科學(xué);2006年02期

10 吳學(xué)文;晏路明;;普通Kriging法的參數(shù)設(shè)置及變異函數(shù)模型選擇方法——以福建省一月均溫空間內(nèi)插為例[J];地球信息科學(xué);2007年03期

相關(guān)博士學(xué)位論文 前1條

1 吳玉鳴;中國(guó)經(jīng)濟(jì)增長(zhǎng)與收入分配差異的空間統(tǒng)計(jì)分析[D];華東師范大學(xué);2004年

相關(guān)碩士學(xué)位論文 前1條

1 祝亞雯;基于地統(tǒng)計(jì)學(xué)理論的旅游景點(diǎn)空間結(jié)構(gòu)研究[D];安徽師范大學(xué);2010年

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