Studying Covariance and Variance Components in the Czech Regions Arrival Tourism Data

Lots of tourism data vary over time for that reason the quality processing techniques are demanded to relate such a series. This study concerns the covariance, resp. variance analysis of arrivals to regions of the Czech Republic using static multivariate methods of partial least squares (PLS), resp. principal component analysis (PCA). In addition, an analysis based on eigenvalue decomposition of Euclidean similarity matrix is employed. The relation of profiles and the direction of processes using linear trends in annual data are studied between arrivals of non-residents and residents. The results are attempted to connect them with some economic parameters and global events.