Geothermal spas as a local development factor, the case of Poland
Kurek, Katarzyna A. ; Heijman, Wim ; Ophem, Johan van; Gędek, Stanisław ; Strojny, Jacek - \ 2020
Geothermics 85 (2020). - ISSN 0375-6505
Geothermal resources - Local development - Poland - Principal Component Analysis - Spas - Switching regression model
This paper investigates whether the endogenous geothermal energy resources used for local tourism facilities are a factor of local development. We answer this research question by examining the local socioeconomic development dynamics in years 1995–2015 in the six selected Polish municipalities that established geothermal spas at different years. A model introduces the concept of switch variables, where a geothermal spa is the assumed switching factor in a municipality's socioeconomic development. The statistical procedures are adopted from factor analysis and trend estimation methodologies. Our conclusions lead to a positive assessment of a geothermal water park's contribution to a municipality's socioeconomic development.
Procrustes analysis in studying sensory-instrumental relations
Dijksterhuis, Garmt - \ 1994
Food Quality and Preference 5 (1994)1-2. - ISSN 0950-3293 - p. 115 - 120.
pre-scaling - Principal Component Analysis - Procrustes Analysis - Sensory-Instrumental relations - standardising
In this paper the relation between a sensory and an instrumental dataset is studied by means of Procrustes Analysis. The method is introduced with emphasis on its application to match two datasets. First the structure of each dataset is studied separately by means of Principal Component Analysis. After standardising the two datasets Procrustes Analysis is used to match the two sets. It is concluded that, though not often used to this end, Procrustes Analysis is a suitable method to study the relations between sensory and instrumental data.
Principal component analysis of TI-curves : Three methods compared
Dijksterhuis, Garmt ; Flipsen, Margo ; Punter, Pieter - \ 1994
Food Quality and Preference 5 (1994)1-2. - ISSN 0950-3293 - p. 121 - 127.
Principal Component Analysis - Principal TI-Curves - Time-Intensity
Perception of time-related aspects of food and beverages is studied by using Time-Intensity (TI) methodology. Time-Intensity-data analysis often consists in summarising the curves of individual subjects by averaging them. For each averaged curve, a number of parameters (e.g. the time of onset, the rate of extinction, the maximum intensity, the time to maximum intensity, etc.) can be computed. In the study reported here, the Time-Intensity curves are analysed by means of a Principal Component Analysis (PCA). The resulting Principal Curves can be interpreted and reflect underlying similarities or differences between the time courses of the tastes involved. The loadings from the PCA's can be used to help in interpreting the Principal Curves and to identify clusters of assessors, or outliers. Non-centred PCA retains both level and variability information from the TI-curves and may be the preferred method for this reason. The centred PCA variants seem to give the tightest clustering of Principal Curves.