Canonical Correlation Analysis for Geographical and Chronological Responses

• Published in: Procedia computer science Vol. 96; pp. 1351 - 1360
• Main Authors: Yamamura, Mariko, Yanagihara, Hirokazu, Solvang, Hiroko Kato, Øien, Nils, Haug, Tore
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2016
• Subjects: Canonical correlation analysis; Multidimensional time-space data; Variable selection; Canonical correlation analysis; Multidimensional time-space data; Variable selection
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2016.08.180

Data containing information about observed location and time are called geographical and chronological data. The purpose of this paper is to propose how we can analyze geographical and chronological data with multiple response variables by innovating the varying coefficient model in canonical correlation analysis. In addition, the variable selection proposed by Hashiyama et al. (2014) is applied to our model. As numerical background, we propose to apply an approach where we use a body condition data set from common minke whales (Balaenoptera acutorostrata acutorostrata) in the Barents Sea (Solvang et al. (2016)). From the estimation results, minke whale body condition is affected by geography in females and by chronology in males, however the geographical effect seems not so strong, and male and female whales gain their body condition as fall approaches, which is the well known as their general habits in the Barents Sea.