1991
DOI: 10.1109/34.67646
|View full text |Cite
|
Sign up to set email alerts
|

Clustering without a metric

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
17
0

Year Published

1994
1994
2014
2014

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 38 publications
(17 citation statements)
references
References 11 publications
0
17
0
Order By: Relevance
“…NMC was preferred over hierarchical clustering and principal components analysis because of the heteroscedasticity among the variances of the parameters (Matthews and Hearne 1991). To assess the validity of the classifications established by NMC, results from the actual data (nonrandom) were compared with those obtained from three sets of data that were created by randomizing the actual data.…”
Section: Discussionmentioning
confidence: 99%
“…NMC was preferred over hierarchical clustering and principal components analysis because of the heteroscedasticity among the variances of the parameters (Matthews and Hearne 1991). To assess the validity of the classifications established by NMC, results from the actual data (nonrandom) were compared with those obtained from three sets of data that were created by randomizing the actual data.…”
Section: Discussionmentioning
confidence: 99%
“…In this section we attempt to outline the similarities and dissimilarities of multivariate methods used in ecotoxicology, focusing on nonmetric multidimensional scaling (MDS, incorporated in the PRIMER computer program; [15]), nonmetric clustering (NMC, incorporated in the Riffle computer program; [16]), and our own approach of canonical ordination using RDA and PRC (incorporated in the CANOCO computer program; [6,9]). …”
Section: Comparison With Other Techniques Used In Mesocosm Experimentsmentioning
confidence: 99%
“…One of these was calculated using Euclidean distance and the other with cosine of vector distance [22,23]. The third test used nonmetric clustering and association analysis (NCAA) as computed by the program RIFFLE [24–27]. Each of these methods assigns individual microcosms to clusters without the intervention of the investigator.…”
Section: Methodsmentioning
confidence: 99%