The Geographic Zones of Maximum and Minimum Temperature in Saudi Arabia: An Application of Cluster Analysis "Ward's Minimum Variance"

1989 ◽  
Vol 2 (1) ◽  
pp. 129-177
Author(s):  
MOHAMMAD AL-JERASH
Keyword(s):  
Cluster Analysis ◽  
Saudi Arabia ◽  
Minimum Temperature ◽  
Minimum Variance

Cluster Analysis in Marketing Research: Review and Suggestions for Application

1983 ◽  
Vol 20 (2) ◽  
pp. 134-148 ◽  
Author(s):  
Girish Punj ◽  
David W. Stewart
Keyword(s):  
Cluster Analysis ◽  
Empirical Work ◽  
Marketing Research ◽  
Minimum Variance ◽  
Alternative Methods ◽  
Research Review ◽  
Preliminary Identification ◽  
Cluster Analytic ◽  
Partitioning Procedure ◽  
Iterative Partitioning

Applications of cluster analysis to marketing problems are reviewed. Alternative methods of cluster analysis are presented and evaluated in terms of recent empirical work on their performance characteristics. A two-stage cluster analysis methodology is recommended: preliminary identification of clusters via Ward's minimum variance method or simple average linkage, followed by cluster refinement by an iterative partitioning procedure. Issues and problems related to the use and validation of cluster analytic methods are discussed.

scholarly journals The skipper butterflies (Lepidoptera: Hesperiidae) of the Reserva Ecológica Leonelo Oviedo, San José, Costa Rica

2019 ◽  
Vol 67 (2SUPL) ◽  
pp. S228-S248
Author(s):  
Luis-Ricardo Murillo-Hiller ◽  
Oscar-Antonio Segura-Bermúdez ◽  
Juan-Diego Barquero ◽  
Federico Bolaños
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
Costa Rica ◽  
Hierarchical Cluster ◽  
R Package ◽  
Minimum Variance ◽  
Shannon Index ◽  
Wet Season ◽  
Identification Guide ◽  
Different Seasons

Hesperiidae is one of the most diverse families of butterflies in Costa Rica, with approximately 486 species. Even so, there are few butterfly lists where this group has been included. In this paper, we present information on seasonality, abundance and natural history features of this family for the Leonelo Oviedo Ecological Reserve (RELO), a 2 ha forest embedded in an urban matrix. Over the course of two years, a monthly sampling was carried out on a 270 m trail across the Reserve from 08:00 to 12:00, collecting all the individuals located within 5 m on each side of the trail. To better represent the richness, individuals were also randomly collected for more than ten years, but the butterflies collected in this way were not included in the statistical analysis. Photographs were taken of all the species in order to provide an identification guide. For the cryptic species, drawings and dissections of the genitalia were made. For the community indexes we used Microsoft Excel and the Shannon index with base two logarithm. For the summary of the monthly data analysis were done according to dry and wet season. For a comparison of richness and abundance we did a g-test to evaluate if there are differences between seasons; however, with the use of the R package vegan a hierarchical cluster analysis was done using the Jaccard index with Wards minimum variance agglomerative method. With R package pvclust the uncertainty of the clusters based on a bootstrap with 10 000 iterations. 423 individuals of 49 species were included in the statistical analysis, from a total of 435 individuals of 58 species. A tendency to greater richness and abundance of skippers was found during the dry season. Through the cluster analysis, it was possible to determine that in relation to the diversity of skippers, both wet seasons are grouped significantly (P = 0.05). The dry seasons are also grouped significantly (P = 0.05). The reserve has connectivity with other green areas via a stream. During the wet season, plant growth increases connectivity, which could lead to the entry of new individuals of different species that are not permanent residents of RELO and establish small populations, increasing the richness and abundance of species. This added to the variation in the occurrence of some species of butterflies in response to seasonal variations and differences in the availability of resources in different seasons explains the grouping of species between seasons.

Segmentation of Sport Center Members in Seoul Based on Attitudes Toward Service Quality

1998 ◽  
Vol 12 (4) ◽  
pp. 273-287 ◽  
Author(s):  
Changhwan Kim ◽  
Susan Y. Kim Korea
Keyword(s):  
Cluster Analysis ◽  
Service Quality ◽  
Minimum Variance ◽  
Analysis Approach ◽  
Chi Square ◽  
Variance Method ◽  
Second Stage ◽  
Usage Patterns ◽  
Member Satisfaction ◽  
Minimum Variance Method

Sport center managers are likely to maximize member satisfaction by developing products or services that are tailored to the different groups of sport center members. A necessary step, then, is to identify different segments of sport center members. This study attempts to identify sport center segments in Seoul, Korea, as determined by the members' attitudes toward 33 service items. A 2-stage cluster analysis approach in which the Ward's minimum variance method is used at the first stage and the K-means method is used at the second stage was employed by using the SPSS statistical package. This yielded 5 member segments that were then analyzed by employing ANOVA or chi-square to determine how they differ in their attitudes toward service attributes, demographics, socioeconomics, motivations, and usage patterns. For those variable responses showing a difference, an analyses of the nature of differences helped profile the members in the 5 segments.

scholarly journals Using high frequency oligonucleotides-targeting active gene (HFO-TAG) markers for genetic evaluation among genotypes (Cucurbita pepo L. and C. maxima L.)

2019 ◽  
Vol 43 (1) ◽  
Author(s):  
Adel Ahmed Elshafei ◽  
Talal Khaled Alateeq ◽  
Rafik Mostafa Habib ◽  
Mohamed Ibrahim Motawei
Keyword(s):  
Cluster Analysis ◽  
Saudi Arabia ◽  
Genetic Variability ◽  
High Frequency ◽  
Cucurbita Pepo ◽  
Genetic Evaluation ◽  
Gene Markers ◽  
Active Gene ◽  
Flavonoid Compounds

Abstract Background Cucurbita spp. is a main source of crypto-xanthine, zeaxanthin lutein folates, and natural poly-phenolic flavonoid compounds. Collection and conservation of genetic variability are helpful in genetic advancement programs. Twenty-two pumpkin genotypes (21genotypes of Cucurbita pepo L. and one genotype of C. maxima L.) were collected from different regions of Saudi Arabia. Fifteen HFO-TAGhigh frequency oligonucleotide–targeting active gene markers were used to analyze genetic variability among 22 pumpkin genotypes. Results A total of 107 alleles were detected by the 15 HFO-TAG markers, an average of 7.133 alleles per primer. Polymorphisms were found in 102 alleles, an average of 6.866 alleles per primer. The PIC values measured from all of the HFO-TAG markers were high, and ranged from 0.8940 to 0.7225, with an average 0.8212 per marker. Conclusions The results of the cluster analysis of pumpkin genotypes were separated into seven groups according to the collection region.

scholarly journals Clustering Analysis of the Survey for Mobility Reasons in the US 1999-2017

2019 ◽  
pp. 1-12
Author(s):  
Liming Xie
Keyword(s):  
United States ◽  
Cluster Analysis ◽  
Survey Data ◽  
Clustering Analysis ◽  
Minimum Variance ◽  
Covariance Estimation ◽  
United States Bureau ◽  
Two Stage ◽  
Average Linkage ◽  
The Us

This paper is to estimate the survey for 98000 addresses from 1999-2017 in United States bureau of Census by using cluster analysis. The analysis is mainly applied by Approximate Covariance Estimation for CLUSTING (ACECLUS), and procedure variables for CLUSTING (VARCLUS) to test some important parameters such as average linkage, two-stage density linkage, Cubic Clustering Criterions (CCC), R-Square, Ward’s minimum variance techniques, as well as Tree procedure for deeper exploring the clusters or variables. After the overall analysis, the results show that there is existence of strong covariate correlation for variables X8 and X15 with respond variable Y (Mobility periods). Hence, Reason “Retired” from survey data is most important impact on mobility other than the reasons “Wanted better neighborhood or less crimes” and “Wanted cheaper housing” that are popular and highly frequent. 

scholarly journals Examining the Spatio-temporal Dynamics of PM2.5 in Saudi Arabia Using Satellite-derived Data: A Cluster Study

2016 ◽  
Author(s):  
Yusuf Aina ◽  
Elhadi Adam ◽  
Fethi Ahmed
Keyword(s):  
Cluster Analysis ◽  
Saudi Arabia ◽  
Particulate Matter ◽  
Urban Areas ◽  
Temporal Dynamics ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
World Health ◽  
Self Organizing Map ◽  
Fine Particulate

The study of the concentrations and effects of fine particulate matter in urban areas have been of great interest to researchers in recent times. This is due to the acknowledgment of the far-reaching impacts of fine particulate matter on public health. Remote sensing data have been used to monitor the trend of concentrations of particulate matter by deriving aerosol optical depth (AOD) from satellite images. The Center for International Earth Science Information Network (CIESIN) has released the second version of its global PM2.5 data with improvement in spatial resolution. This paper revisits the study of spatial and temporal variations in particulate matter in Saudi Arabia by exploring the cluster analysis of the new data. Cluster analysis of the PM2.5 values of Saudi cities is performed by using Anselin local Moran’s I statistic. Also, the analysis is carried out at the regional level by using self-organizing map (SOM). The results show an increasing trend in the concentrations of particulate matter in Saudi Arabia, especially in some selected urban areas. The eastern and south-western parts of the Kingdom have significantly clustering high values. Some of the PM2.5 values have passed the threshold indicated by the World Health Organization (WHO) standard and targets posing health risks to Saudi urban population.

Understory plant community classifications as predictors of forest site quality for lodgepole pine and white spruce in west-central Alberta

1988 ◽  
Vol 18 (7) ◽  
pp. 875-887 ◽  
Author(s):  
George H. La Roi ◽  
Wayne L Strong ◽  
Donald J. Pluth
Keyword(s):  
Cluster Analysis ◽  
Lodgepole Pine ◽  
White Spruce ◽  
Minimum Variance ◽  
Forest Site ◽  
Percent Cover ◽  
Forest Types ◽  
Understory Species ◽  
West Central ◽  
Species Cover

Understory vegetation of 103 lodgepole pine (Pinuscontorta Loudon var. latifolia Engelm.) and white spruce (Piceaglauca (Moench) Voss) stands, 70–150 years old, in a 16 000 km2 region of west-central Alberta was classified by 14 methods using species cover or log2 cover classes. Six classifications, including five selected by dendrogram and ordination elucidation of understory community types (UCTs), were evaluated by analysis of variance to identify UCTs with significantly different site indices of pine and spruce. Each classification consists of three to five UCTs, referable to two forest types, both levels distinguished by differences in constancy and cover of understory species. Significant differences (P < 0.05) in pine site index at 70 years occur between UCTs belonging to the same and different forest types, using divisive two-way indicator species analysis (TSL) and agglomerative furthest neighbour (FNL) and minimum variance (MVL) cluster analysis classifications, all based on log2 cover classes. Comparable differences between UCTs for spruce occur within one forest type, using FNL, MVL, and minimum variance cluster analysis based on raw percent cover (MVR). Ordination of stands based on understory species cover reveals that spatially segregated UCTs usually have significantly different site indices. If a single classification method is desired for both lodgepole pine and white spruce, MVL appears most suitable for predicting site indices in the region.

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