Nonlinear Principal Component Analysis for Geographically Weighted Temporal‑spatial Data - Krzyśko, Mirosław; Łukaszonek, Wojciech; Ratajczak, Waldemar; Wołyński, Waldemar (Acta Universitatis Lodziensis. Folia Oeconomica, 2018)
Schölkopf, Smola and Müller (1998) have proposed a nonlinear principal component analysis (NPCA) for fixed vector data. In this paper, we propose an extension of the aforementioned analysis to temporal‑spatial data and weighted temporal‑spatial data. To illustrate the proposed theory, data describing the condition of state of higher education in 16 Polish voivodships in the years 2002–2016 are used.