A distance correlation index of spatial dependence for compositional data

Papers in Regional ScienceVolume 98, Issue 6 p. 2371-2389 FULL ARTICLE A distance correlation index of spatial dependence for compositional data M. Simona Andreano, Corresponding Author M. Simona Andreano s.andreano@unimercatorum.it orcid.org/0000-0003-0748-1524 Department of Economics, University Mercatorum, Italy Correspondence M. Simona Andreano, Department of Economics, University Mercatorum, Italy, Piazza Mattei 10, Rome IT-00186. Italy Email: s.andreano@unimercatorum.itSearch for more papers by this authorRoberto Benedetti, Roberto Benedetti orcid.org/0000-0003-0763-819X Department of Economics, University of Chieti-Pescara, ItalySearch for more papers by this authorFederica Piersimoni, Federica Piersimoni orcid.org/0000-0001-7075-4893 Directorate Methodology and Statistical Process Design, ISTAT, ItalySearch for more papers by this author M. Simona Andreano, Corresponding Author M. Simona Andreano s.andreano@unimercatorum.it orcid.org/0000-0003-0748-1524 Department of Economics, University Mercatorum, Italy Correspondence M. Simona Andreano, Department of Economics, University Mercatorum, Italy, Piazza Mattei 10, Rome IT-00186. Italy Email: s.andreano@unimercatorum.itSearch for more papers by this authorRoberto Benedetti, Roberto Benedetti orcid.org/0000-0003-0763-819X Department of Economics, University of Chieti-Pescara, ItalySearch for more papers by this authorFederica Piersimoni, Federica Piersimoni orcid.org/0000-0001-7075-4893 Directorate Methodology and Statistical Process Design, ISTAT, ItalySearch for more papers by this author First published: 23 May 2019 https://doi.org/10.1111/pirs.12451Citations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstracten Geographical data in economic, social or environmental sciences are usually recorded as compositions, i.e. relative frequencies, and a common inquiring problem concerns the analysis of these data over different geographical regions. In the present paper we define a new statistical test to verify spatial dependence of such geographical distributions based on distance correlation, a recently introduced measure of dependence between random vectors. The proposed index computes the non-linear spatial distance between distributions and can be applied on compositional frequency distributions. Simulations and an application on Italian electoral data are presented, to illustrate the capabilities of the proposed test to detect spatial dependence. Resumenes Los datos geográficos de las ciencias económicas, sociales o ambientales suelen registrarse como composiciones, es decir, frecuencias relativas, y un problema común que se plantea a menudo es el análisis de estos datos en diferentes regiones geográficas. En el presente artículo se define una nueva prueba estadística para verificar la dependencia espacial de tales distribuciones geográficas, en función de la correlación de distancias, que es una medida introducida recientemente de dependencia entre vectores aleatorios. El índice propuesto calcula la distancia espacial no lineal entre distribuciones y puede aplicarse a distribuciones de frecuencias de composición. Se presentan simulaciones y una aplicación para datos electorales italianos a fin de ilustrar las capacidades de la prueba propuesta para detectar la dependencia espacial. 抄録ja 経済学、社会学、環境科学における地理データは、通常は構成要素、すなわち相対度数として記録され、頻繁に尋ねられる問題は、異なる地理的地域全体のこれらのデータの分析に関するものである。本稿では、ランダムベクトル間の依存度の測定距離相関に基づく地理的分布の空間依存を検証する新規の統計的検定方法を定義する。提案した指数は、分布間の非線形空間的距離を計算し、構成要素の頻度分布に適用することができる。イタリアの選挙データに応用したシミュレーションを提示し、提案した検定法の空間依存性を検出する能力を証明する。 Citing Literature Volume98, Issue6December 2019Pages 2371-2389 RelatedInformation