On the partitioning of squared Euclidean distance and its applications in cluster analysis

Psychometrika ◽  
1989 ◽  
Vol 54 (1) ◽  
pp. 9-23 ◽  
Author(s):  
Randy L. Carter ◽  
Robin Morris ◽  
Roger K. Blashfield
Keyword(s):  
Cluster Analysis ◽  
Euclidean Distance ◽  
Squared Euclidean Distance

EFFECTIVENESS OF ACADEMIC TEACHING IN THE FIELD OF AGRICULTURAL SCIENCES

2018 ◽  
Vol XX (1) ◽  
pp. 104-110 ◽  
Author(s):  
Piotr Pietrzak
Keyword(s):  
Higher Education ◽  
Cluster Analysis ◽  
Pilot Study ◽  
Euclidean Distance ◽  
Public Universities ◽  
Full Time ◽  
Academic Teaching ◽  
Empirical Verification ◽  
Agricultural Sciences ◽  
Squared Euclidean Distance

The paper discusses the effectiveness of teaching in fields representing agricultural sciences. Empirical verification was based on data taken from the Ministry of Science and Higher Education. The research is a pilot study and concerns 1935 graduates of 10 Polish public universities, who obtained a second-cycle full-time studies diploma in 2015. Cluster analysis was performed using Ward’s method and squared Euclidean distance. The conducted procedure allowed to distinguish three clusters of fields differing in level of effectiveness of teaching. In general, the highest effectiveness in the studied group of fields of science was characterized by those that were run through universities located in the capital and cities over 500,000 residents.

scholarly journals ANALISIS KLASTER METODE WARD DAN AVERAGE LINKAGE DENGAN VALIDASI DUNN INDEX DAN KOEFISIEN KORELASI COPHENETIC (Studi Kasus: Kecelakaan Lalu Lintas Berdasarkan Jenis Kendaraan Tiap Kabupaten/Kota di Jawa Tengah Tahun 2018)

2019 ◽  
Vol 8 (4) ◽  
pp. 486-495
Author(s):  
Sisca Indah Pratiwi ◽  
Tatik Widiharih ◽  
Arief Rachman Hakim
Keyword(s):  
Cluster Analysis ◽  
Euclidean Distance ◽  
Traffic Accidents ◽  
Optimal Number ◽  
Cophenetic Correlation ◽  
Central Java ◽  
Average Linkage ◽  
Linkage Method ◽  
Ward Method ◽  
Squared Euclidean Distance

Based on Central Java Regional Police data, traffic accidents from 2017 to 2018 increased from 17.522 to 19.016 or 8,54 percent. To reduce the number of traffic accidents in Central Java, the initial step was carried out by grouping districts/cities that had the same accident level characteristics based on vehicle type with cluster analysis. The ward and average linkage method is a hierarchical cluster analysis method. ward method can maximize cluster homogeneity. While the average linkage method can generate clusters with small cluster variants. In this study using a measure of squared euclidean distance to measure the similarity between pairs of objects. To determine the quality of clustering results, the validation dunn index and cophenetic coefficients corelation are used. Based on the results of the clustering, the optimal number of clusters is obtained at q = 5 for the average linkage method with the results of validation dunn index = 0,08571196 and the rcoph = 0,687458. Keywords: Accidents, Cluster Analysis, Ward Method, Average linkage, Squared Euclidean Distance, Dunn Index, Cophenetic Correlation Coefficient

scholarly journals A test for multigroup comparison using partial least squares path modeling

2019 ◽  
Vol 29 (3) ◽  
pp. 464-477 ◽  
Author(s):  
Michael Klesel ◽  
Florian Schuberth ◽  
Jörg Henseler ◽  
Bjoern Niehaves
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Statistical Power ◽  
Euclidean Distance ◽  
Geodesic Distance ◽  
Group Differences ◽  
Path Modeling ◽  
Content Type ◽  
Significance Level ◽  
Squared Euclidean Distance

Purpose People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches. Design/methodology/approach The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches. Findings Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach. Research limitations/implications Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations. Originality/value This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

A Modified Version of the K-Means Algorithm Based on the Shape Similarity Distance

2013 ◽  
Vol 457-458 ◽  
pp. 1064-1068
Author(s):  
Dan Li ◽  
Xin Bao Li
Keyword(s):  
Cluster Analysis ◽  
Euclidean Distance ◽  
Distance Measure ◽  
Shape Similarity ◽  
Popular Method ◽  
Similarity Estimation ◽  
Metric Distance ◽  
Similarity Distance ◽  
Shape Data ◽  
Better Than

K-means Algorithm is a popular method in cluster analysis, and it is most based on the Euclidean distance. In this paper, a modified version of the K-means algorithm based on the shape similarity distance (SSD-K-means) is presented. The shape similarity distance is one kind of non-metric distance measure for similarity estimation based on the characteristic of differences. To demonstrate the effectiveness of the method we proposed, this new algorithm has been tested on three shape data datasets. Experiment results prove that the performance of the SSD-K-means is better than those of the classical K-means algorithm based on the traditional Euclidean and Manhattan distances.

Rate-Compatible Punctured Ring Convolutional Coded Continuous Phase Modulation

2012 ◽  
Vol 195-196 ◽  
pp. 217-220
Author(s):  
Lei Zhang ◽  
Man Ping Tong ◽  
Hong Bo Wang
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Phase Modulation ◽  
Euclidean Distance ◽  
Convolutional Codes ◽  
Continuous Phase ◽  
Transmission Efficiency ◽  
Continuous Phase Modulation ◽  
Simulation Results ◽  
Squared Euclidean Distance

In this paper, continuous phase modulation (CPM) with rate-compatible punctured ring convolutional codes is investigated. Some typical schemes with maximum normalized minimum squared euclidean distance (NMSED) are searched and given. The performance of bit error rate for rate-compatible punctured ring convolutional coded CPM on AWGN channel is simulated, and simulation results show that this system can provide good performance of bit error rate and variable-rate capabilities. Furthermore, simulation results also prove that the transmission efficiency increases when code rate is decreasing.

Clustering of Composite Protein Films and their Packaging Properties

2014 ◽  
Vol 607 ◽  
pp. 37-42
Author(s):  
Qiao Lei ◽  
Yu Ting Zhang ◽  
Jia Zhen Pan ◽  
Jian Qiang Bao ◽  
Zhi Ying Huang
Keyword(s):  
Cluster Analysis ◽  
Whey Protein ◽  
Euclidean Distance ◽  
Gas Permeability ◽  
Composite Films ◽  
Sodium Caseinate ◽  
Protein Isolate ◽  
The Other ◽  
Protein Films ◽  
Processing Techniques

Cases of 30 whey protein isolate-sodium caseinate-glycerol composite protein films based on different ingredients and processing techniques, and their packaging properties were analyzed by Q and R cluster analysis, respectively. The results verified that there was a correlation in either 30 cases or 7 indexes of packaging performance, which contributed to a scientific sorting. 30 cases could be divided into 5 groups by Q cluster analysis with the Euclidean distance at 40, in which case 28 and 30 exhibited the highest similarity. On the other hand R cluster analysis in packaging performance indicated that gas permeability and haze values of composite films tended to be more similar than the others.

scholarly journals TAXONOMIC REVISION OF NIGERIAN SPECIES OF Capsicum L. BASED ON SOME MORPHOLOGICAL CHARACTERS

2021 ◽  
Vol 5 (2) ◽  
pp. 43-46
Author(s):  
Adeyinka O. Adepoju ◽  
Tunde J. Ogunkunle ◽  
Abiola G. Femi-Adepoju
Keyword(s):  
Genetic Variation ◽  
Euclidean Distance ◽  
Germplasm Collection ◽  
Taxonomic Status ◽  
Taxonomic Revision ◽  
Morphological Characters ◽  
Infrageneric Classification ◽  
Reproductive Morphology ◽  
Operational Taxonomic Units ◽  
Squared Euclidean Distance

Species of Capsicum L. are closely related plants whose taxonomic status has remained controversial among different taxonomists. This study was designed to examine the taxonomic status of the species of Capsicum in Nigeria in order to establish the genetic variation between the species for the purpose of identification, as well as review the infrageneric classification (INC) of the members of the genus. Germplasm collection of the seeds of five cultivars of Capsicum were regenerated and nurtured to fruiting. Variations in their vegetative and reproductive morphology were macroscopically evaluated in replicates of 30 individuals per cultivar for each character, which equals 150 samples altogether. The cultivars of each species was hierarchically clustered as operational taxonomic units (OTUs) using Ward’s method with squared Euclidean distance. Artificial key was also constructed for the identification of the species in the genus. The twenty-three (23) morphological characters adopted gave useful insights into the INC of the species and were sufficiently diagnostic of the species as evidenced by the artificial key. Through this study, some light has been shed on the delimitation of species and varieties of the Nigerian Capsicum.

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