scholarly journals Assessment of the Development of the European Oecd Countries with the Application of Linear Ordering and Ensemble Clustering of Symbolic Data

2019 ◽  
Vol 19 (2) ◽  
pp. 117-133
Author(s):  
Marcin Pełka
Keyword(s):  
Cluster Analysis ◽  
Multidimensional Scaling ◽  
Human Development Index ◽  
Oecd Countries ◽  
Linear Ordering ◽  
Ensemble Clustering ◽  
Single Model ◽  
Symbolic Data ◽  
Development Analysis ◽  
Complex Indicators

Abstract The research background of the paper covers the development of a country, that can be measured in various ways. Simple indicators, like GDP and also complex indicators such as HDI (human development index), can be used to measure country development. However, usually countries are divided into groups via setting some arbitrary levels of final measure. What is more, the composite (complex) indices have some problems and errors. The main purpose of the paper is the assessment of the development of the selected European OECD countries with the application of the linear ordering and ensemble clustering of symbolic data as well as comparison of the ensemble clustering with a single model. Research methodology covers linear ordering with the application of multidimensional scaling for a visualisation of results and ensemble clustering for symbolic data. The results are compared according to adjusted Rand and silhouette indices. The obtained results show that ensemble clustering for symbolic data can be a useful tool in country development analysis and allows reaching better results than a single model. The novelty of the proposed approach is to use a cluster analysis to obtain the clusters of countries with similar variables’ values (indicators of development) and the application of multidimensional scaling for symbolic data in order to visualise linear ordering results.

Statistical Analysis of Personnel Data Using Factor Scoring Cluster Analysis and Multidimensional Scaling

1973 ◽  
Author(s):  
Robert R. Read ◽  
Richard S. Elster ◽  
Gerald L. Musgrave ◽  
John W. Creighton ◽  
William H. Githens
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
Multidimensional Scaling

scholarly journals Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling

2014 ◽  
Vol 71 (1) ◽  
pp. 38-43 ◽  
Author(s):  
Anderson Rodrigo da Silva ◽  
Paulo Roberto Cecon ◽  
Carlos Tadeu dos Santos Dias ◽  
Mário Puiatti ◽  
Fernando Luiz Finger ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Multidimensional Scaling

scholarly journals Distribution of naked amoebae in the soils of the steppe zone of Ukraine

2020 ◽  
pp. 159-166
Author(s):  
M. Patsyuk ◽  
Keyword(s):  
Cluster Analysis ◽  
Multidimensional Scaling ◽  
Species Complex ◽  
Steppe Zone ◽  
Common Species ◽  
Molecular Clusters ◽  
The Other ◽  
Steppe Region ◽  
Species Complexes ◽  
Naked Amoebae

As a result of the study, in the steppe zone of Ukraine (Odessa, Mykolaiv, Kirovohrad region), 12 species of naked amoebas were identified, which according to the modern Eukaryot system belong to three molecular clusters Tubulinea Smirnov et al., 2005, Discosea Cavalier-Smith, 2004., Discoba Simpson and Hampl et al., 2009. This species Vahlkampfia sp. (1), Vahlkampfia sp. (2), Deuteramoeba mycophaga Page, 1988, Saccamoeba stagnicola Page, 1974, Vexillifera sp., Vannella sp. Ripellaplatypodia Smirnov, Nassonova, Chao et Cavalier-Smith, 2007, Cochliopodium sp. (1), Mayorella sp., Thecamoeba striata Penard, 1890, Stenamoeba stenopodia (Page, 1969) Smirnov et al., 2007, Acanthamoeba sp. (1). In the studied steppe soils, the most common were Vahlkampfia sp. (2), S. stenopodia, Vahlkampfia sp. (1), Vexillifera sp., Cochliopodium sp. (1); the least common – R. platypodia, D. mycophaga, T. striata, Mayorella sp. As a result of the cluster analysis, it was found that the largest share of common species is observed between Mykolaiv and Kirovograd regions (0.71) and Odessa and Kirovograd regions (0.53); the smallest is between the Odessa and Mykolaiv regions (0.43). According to the results of cluster analysis, the faunistic complexes of soil species of amoebae of the steppe region of Ukraine are united into two clusters: one of them being complexes characteristic of the Odessa region, and the other complexes of the Mykolaiv and Kirovograd regions. According to the results of nonparametric multidimensional scaling, it is established that the species complex of soil amoebae in the Kirovograd and Mykolaiv regions is determined by the increased soil temperature and acidity, compared to the Odessa region. As for moisture, this factor has little effect on the species complexes amoebae steppe region of Ukraine.

scholarly journals Study of the Tax Wedge in EU and other OECD Countries, Using Cluster Analysis

2018 ◽  
Vol 238 ◽  
pp. 687-696
Author(s):  
Claudia Florina Radu ◽  
Cristina Fenişer ◽  
Klaus Bruno Schebesch ◽  
Florin Fenişer ◽  
Florin Marian Dobrea
Keyword(s):  
Cluster Analysis ◽  
Oecd Countries

Evaluating dialect in discourse: Teachers' and teenagers' responses to young English speakers in Wales

1999 ◽  
Vol 28 (3) ◽  
pp. 321-354 ◽  
Author(s):  
PETER GARRETT ◽  
NIKOLAS COUPLAND ◽  
ANGIE WILLIAMS
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
Multidimensional Scaling ◽  
English Speakers ◽  
Additive Effects ◽  
School Students ◽  
Dialect Variation ◽  
Regional Dialect ◽  
English Dialect

School students (15–16 years) in six regions of Wales were recorded telling stories in their local English dialects. Some of these narratives were used as samples representing the main English dialect regions in Wales. Comparable groups of students (n = 169) and a group of teachers (n = 47) rated the audio-recorded speakers on a number of scales of affiliation, status, and Welshness. Statistical analysis of their ratings, employing cluster analysis and multidimensional scaling, made it possible to detect some of the competing or additive effects of dialect and narrative features. Judgments of “Welshness” of the speaker/narratives were grounded in the regional dialect properties; but other judgments, such as the likability of the speakers, tended to draw on features of both dialect and narrative. In addition, comparison of students and teachers revealed differences in their evaluations of particular dialect communities and the characteristics of the narratives. The findings illustrate the importance of approaching the analysis of dialect variation within the broader context of speech and discourse performance.

The influence of health on economic growth from the perspective of sustainable development: a case of OECD countries

2020 ◽  
Vol 16 (3) ◽  
pp. 181-194 ◽  
Author(s):  
Seda Yıldırım ◽  
Durmus Cagri Yildirim ◽  
Hande Calıskan
Keyword(s):  
Economic Growth ◽  
Cluster Analysis ◽  
Sustainable Development ◽  
Health Status ◽  
Life Expectancy ◽  
Oecd Countries ◽  
Content Type ◽  
Life Expectancy At Birth ◽  
Lower Health

PurposeThis study aims to explain the role of health on economic growth for OECD countries in the context of sustainable development. Accordingly, the study investigates the relationship between health and economic growth in OECD countries.Design/methodology/approachThis study employed cluster analysis and econometric methods. By cluster analysis, 12 OECD countries (France, Germany, Finland, Slovenia, Belgium, Portugal, Estonia, Czech Republic, Hungary, South Korea, Poland and Slovakia) were classified into two clusters as high and low health status through health indicators. For panel threshold analysis, the data included growth rates, life expectancy at birth, export rates, population data, fixed capital investments, inflation and foreign direct investment for the period of 1999–2016.FindingsThe study determined two main clusters as countries with high health status (level) and low health status (level), but there was no threshold effect in clusters. It was concluded that an increase in the life expectancy at birth of countries with higher health status had no significant impact on economic growth. However, the increase in the life expectancy at birth of countries with lower health status influenced economic growth positively.Research limitations/implicationsThis study used data that including period of 1999–2016 for OECD countries. In addition, the study used cluster analysis to determine health status of countries, and then panel threshold analysis was preferred to explain significant relations.Originality/valueThis study showed that the role of health on economic growth can change toward country groups as higher and lower health status. It was proved that higher life expectancy can influence economic growth positively in countries with worse or low health status. In this context, developing countries, which try to achieve sustainable development, should improve their health status to achieve economic and social development at the same time.

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