翻訳と辞書 Words near each other ・ Moran of the Marines ・ Moran process ・ Moran River ・ Moran Roth ・ Moran Sarkar ・ Moran Shipping Agencies ・ Moran State Park ・ Moran Station ・ Moran sternwheelers ・ Moran Town ・ Moran Township ・ Moran Township, Michigan ・ Moran Township, Todd County, Minnesota ・ Moran v Pyle National (Canada) Ltd ・ Moran v. Household International, Inc. ・ Moran's I ・ Moran's Oyster Cottage ・ Moran's theorem ・ Moran, British Columbia ・ Moran, California ・ Moran, Indiana ・ Moran, Israel ・ Moran, Kansas ・ Moran, Texas ・ Moran, Virginia ・ Moran, Wyoming ・ Morana ・ Morana (film) ・ Morana Dam ・ Moranak Meada Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Moran's I ： ウィキペディア英語版 Moran's I In statistics, Moran's ''I'' is a measure of spatial autocorrelation developed by Patrick Alfred Pierce Moran. Spatial autocorrelation is characterized by a correlation in a signal among nearby locations in space. Spatial autocorrelation is more complex than one-dimensional autocorrelation because spatial correlation is multi-dimensional (i.e. 2 or 3 dimensions of space) and multi-directional. == Definition == Moran's ''I'' is defined as :$I\; =\; \backslash frac\; w\_\}\; \backslash frac\; w\_(X\_i-\backslash bar\; X)\; (X\_j-\backslash bar\; X)\}$ where $N$ is the number of spatial units indexed by $i$ and $j$; $X$ is the variable of interest; $\backslash bar\; X$ is the mean of $X$; and $w\_$ is an element of a matrix of spatial weights. The expected value of Moran's ''I'' under the null hypothesis of no spatial autocorrelation is :$E(I)\; =\; \backslash frac$ Its variance equals :$\backslash operatorname(I)\; =\; \backslash frac\; w\_)^2\}\; -\; (E(I))^2$ where :$S\_1\; =\; \backslash frac\; \backslash sum\_\; \backslash sum\_\; (w\_+w\_)^2$ :$S\_2\; =\; \backslash sum\_\; (\; \backslash sum\_\; w\_\; +\; \backslash sum\_\; w\_)^2$ :$S\_3\; =\; \backslash frac\; (x\_i\; -\; \backslash bar\; x)^4\}\; (x\_i\; -\; \backslash bar\; x)^2)^2\}$ :$S\_4\; =\; (N^2-3N+3)S\_1\; -\; NS\_2\; +\; 3\; (\backslash sum\_\; \backslash sum\_\; w\_)^2$ :$S\_5\; =\; (N^2-N)\; S\_1\; -\; 2NS\_2\; +\; 6(\backslash sum\_\; \backslash sum\_\; w\_)^2$ 〔Cliff and Ord (1981), Spatial Processes, London〕 Negative values indicate negative spatial autocorrelation and the inverse for positive values. Values range from −1 (indicating perfect dispersion) to +1 (perfect correlation). A zero value indicates a random spatial pattern. For statistical hypothesis testing, Moran's ''I'' values can be transformed to Z-scores in which values greater than 1.96 or smaller than −1.96 indicate spatial autocorrelation that is significant at the 5% level. Moran's ''I'' is inversely related to Geary's ''C'', but it is not identical. Moran's ''I'' is a measure of global spatial autocorrelation, while Geary's ''C'' is more sensitive to local spatial autocorrelation. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Moran's I」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.