scholarly journals Average Linkage Cluster Analysis

2020 ◽  
Author(s):  
Keyword(s):  
Cluster Analysis ◽  
Average Linkage ◽  
Linkage Cluster

scholarly journals Diversity of milk traits in 25 goat breeds

2022 ◽  
Vol 335 ◽  
pp. 00009
Author(s):  
Ferdy Saputra ◽  
Anneke Anggraeni
Keyword(s):  
Cluster Analysis ◽  
Protein Content ◽  
Statistical Approach ◽  
Fat Content ◽  
High Fat ◽  
Milk Traits ◽  
Preference Analysis ◽  
Average Linkage ◽  
Linkage Cluster ◽  
Relationship Of

Goats are livestock that is mostly raised by small farmers in Indonesia because they are easier to raise. Apart from having the potential to become meat, several breeds of which are kept as milk-purpose. Milk traits of each breed differ from one another. Therefore, this study tried to observe genetic differences of 25 goat breeds with statistical approach. Information about milk traits from 25 goat breeds is obtained from published journal. Multidimensional preference analysis and average linkage cluster analysis were performed using SAS 9.4 to determine the differences in goat breeds from three traits, namely milk yield, fat content, and protein content. Multidimensional preference analysis was able to see the advantages of breeds from the three observed traits. Goat breeds with superior milk yields are Saanen, Camosciata delle Alpi, and Charmoisée. Sarda Primitiva, Sarda, Etawah Grade have high fat content in milk. In addition, Arsi-Bale and Somali have high protein content. Average linkage cluster analysis is able to observe the genetic relationship of goat breeds based on three traits. According to average linkage cluster analysis, we found four clusters for goat breeds in this study. With existing statistical approaches, we can evaluate genetic diversity in milk traits.

Personality Types in Data from California Psychological Inventory as Defined by Cluster Analysis

1981 ◽  
Vol 48 (1) ◽  
pp. 115-118 ◽  
Author(s):  
Maurice Lorr ◽  
Gary K. Burger
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Personality Types ◽  
California Psychological Inventory ◽  
Standard Score ◽  
Average Linkage ◽  
Cluster Analytic ◽  
Linkage Cluster ◽  
Psychological Inventory

The study compared the three personality types delineated by Burger and Cross by obverse factor analysis with those disclosed by an average linkage cluster analytic technique. The data were from three subsamples of 85 men who completed the California Psychological Inventory for Burger and Cross. The standard score profiles within each sample were intercorrelated and then cluster analyzed. Four profile types were replicated across the three subsamples. Two of the types, labeled antisocial and well-adjusted, corresponded fairly closely to the Burger-Cross types. There were differences in the number of types generated, in the proportion of individuals classified, and in the profile shapes.

Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis

2021 ◽  
Author(s):  
S.R. Singh ◽  
S. Rajan ◽  
Dinesh Kumar ◽  
V.K. Soni
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Single Linkage ◽  
Pod Yield ◽  
Diversity Assessment ◽  
Single Linkage Cluster ◽  
Linkage Cluster

Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement.Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity.Result: Principal component analysis revealed that first five principal components possessed Eigen value greater than 1, cumulatively contributed greater than 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.

Computer-aided RAPD fingerprinting of accessions from the ryegrass–fescue complex

1997 ◽  
Vol 129 (3) ◽  
pp. 257-265 ◽  
Author(s):  
G. šIFFELOVÁ ◽  
M. PAVELKOVÁ ◽  
A. KLABOUCHOVÁ ◽  
I. WIESNER ◽  
V. NAšINEC
Keyword(s):  
Festuca Arundinacea ◽  
Dna Isolation ◽  
Similarity Matrix ◽  
Rapd Profile ◽  
Average Linkage ◽  
Computer Image Processing ◽  
Computer Aided ◽  
Primary Output ◽  
Taxonomic Groups ◽  
Linkage Cluster

RAPD (Randomly Amplified Polymorphic DNA) assay of 32 cultivar accessions from the ryegrass–fescue (Lolium–Festuca) complex was accomplished using ten decamer primers to assess (i) the power of RAPD technology to discriminate between individual commercial accessions and to produce cultivar fingerprinting, (ii) the degree of relatedness of accessions based on RAPD profiles in comparison with other existing classifications, and (iii) the possibility of automation of RAPD technology.The variation of the correlation coefficient r as the primary output from the automated RAPD-profile processing summarizes variability derived from DNA isolation, the RAPD reaction, and final computer-image processing of RAPD profiles. The AII (Accession Identity Interval) of r for accession Festuca arundinacea cv. Lekora was determined experimentally and the value obtained was accepted as a valid interval for all the other accessions studied. In order to evaluate the discrimination potential of all ten primers together, a pooled-similarity matrix was computed. Employing this approach, we achieved 100% discrimination between all 35 accessions when using all ten primers. A dendrogram for all 35 accessions was obtained using average linkage cluster analysis (UPGMA – Unweighted Pair Group Method with Arithmetic Means). This procedure successfully produced smaller groups of higher taxonomic homogeneity. The relationships between the Lolium–Festuca accessions were also revealed by principal coordinate analysis (PCO) based on absorbance profiles from the RAPD assay. Again, all accessions were well separated, recognising even subspecies relationships. In general, PCO analysis confirmed the inferences made from the UPGMA method.We successfully applied the computer-aided system of RAPD assay, based on an IBM PC computer, for discrimination of cultivars as well as for description of DNA-based relationships of accessions from various taxonomic groups of the Lolium–Festuca complex.

Identifying Rogue Air Temperature Stations Using Cluster Analysis of Percentile Trends

2005 ◽  
Vol 18 (8) ◽  
pp. 1275-1287 ◽  
Author(s):  
Scott M. Robeson ◽  
Jeffrey A. Doty
Keyword(s):  
Cluster Analysis ◽  
Air Temperature ◽  
Large Body ◽  
Large Temperature ◽  
Daily Maximum ◽  
Climatic Data ◽  
Single Linkage ◽  
Frequency Distributions ◽  
Temperature Trends ◽  
Average Linkage

Abstract A new and efficient method for identifying “rogue” air temperature stations—locations with unusually large air temperature trends—is presented. Instrumentation problems and spatially unrepresentative local climates are sometimes more apparent in air temperature extremes, yet can have more subtle impacts on variations in mean air temperature. As a result, using data from over 1300 stations in North America, the tails of daily air temperature frequency distributions were examined for unusual trends. In particular, linear trends in the 5th percentile of daily minimum air temperature during the winter months and the 95th percentile of daily maximum air temperature during the summer were analyzed. Cluster analysis then was used to identify stations that were distinct from other locations. Both single- and average linkage clustering were evaluated. By identifying individual stations along the entire periphery of the percentile trend space, single-linkage clustering appears to produce better results than that of average linkage. Average linkage clustering tends to group together several stations with large trends; however, only a handful of these stations appear distinctly different from the large body of trends toward the center of the percentile trend space. Maps of the rogue stations show that most are in close proximity to numerous other stations that were not grouped into the rogue cluster, making it unlikely that the unusually large temperature trends were due to regional climatic variations. As with all approaches for evaluating data quality, time series plots and station history information also must be inspected to more fully understand inhomogeneous variations in historical climatic data.

scholarly journals Consumer Preferences for Longevity Information and Guarantees on Cut Flower Arrangements

HortScience ◽  
2014 ◽  
Vol 49 (6) ◽  
pp. 769-778 ◽  
Author(s):  
Alicia L. Rihn ◽  
Chengyan Yue ◽  
Charles Hall ◽  
Bridget K. Behe
Keyword(s):  
Cluster Analysis ◽  
Choice Experiment ◽  
Consumer Preferences ◽  
Value Added ◽  
Single Species ◽  
Market Potential ◽  
Vase Life ◽  
Cut Flower ◽  
Cut Flowers ◽  
Linkage Cluster

Choice experiments were conducted to explore the market potential or value added when using longevity information and guarantees on cut flower arrangements in the retail setting. The objective of our study was to determine consumer preferences and willingness to pay for different vase life longevities and guarantees on cut flower arrangements. The choice experiment data were collected using online surveys with 525 U.S. consumers in July 2011. The choice experiment scenarios included single species or mixed species cut flower arrangements with varying vase life longevity (5 to 7 days, 8 to 10 days, 11 to 14 days), presence or absence of vase life longevity guarantee, personal or gift use, and price range ($7.99 to $11.99, $34.99 to $43.99). Two types of arrangements were used in the experiment, mixed arrangements consisting of different species of cut flowers and single-species arrangements consisting of six red roses plus a filler flower. We analyzed the data with a mixed logit model and Ward’s linkage cluster analysis. As expected, participants were willing to pay higher prices for cut flower arrangements with longer vase life longevity. The presence of a guarantee improved participants’ probability of selecting the corresponding cut flower arrangement. Using Ward’s linkage cluster analysis, we found there were three distinct consumer clusters: guarantee seekers (49% of the sample), value-conscious consumers (31%), and spenders (20%). Among the three clusters, guarantee seekers were more likely to select cut flower arrangements with guarantees. Value-conscious consumers were interested in both guarantees and longevity indicators. Spenders were least interested in longevity indicators and guarantees. We conclude floral retailers could successfully implement the use of longevity indicators and guarantees to increase consumer interest in cut flowers and generate profits. Target marketing strategies could then be developed by floral retailers to attract different consumer clusters.

scholarly journals PENGELOMPOKAN DESA/KELURAHAN DI KOTA DENPASAR MENURUT INDIKATOR PENDIDIKAN

2016 ◽  
Vol 5 (2) ◽  
pp. 38
Author(s):  
NI WAYAN ARIS APRILIA A.P ◽  
I GUSTI AYU MADE SRINADI ◽  
KARTIKA SARI
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
The Other ◽  
Single Linkage ◽  
Complete Linkage ◽  
Hierarchical Method ◽  
Average Linkage ◽  
Different Characteristics

Cluster analysis is one of data analysis used to classify objects in clusters which has objects with the same characteristics, whereas the other cluster has different characteristics. One part of the method of analysis cluster is hierarchy method. In a hierarchical method there are methods of linkage in the form of incorporation. Generally, methods of linkage is divided into 5 methods: single linkage, complete linkage, average linkage, Ward and centroid.  The purpose of this study was to determine the best method of linkage among the method of single linkage, complete linkage, average linkage, and Ward, using Euclidean and Pearson proximity distance. Base on the smallest value of CTM (Cluster Tightness Measure), the best method of linkage as a result of this research was average linkage in Pearson distance.

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