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canonical variate analysis

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Journal Article

Biofacies Analysis of Presence or Absence Data Through Canonical Variate Analysis

Martin A. Buzas
Published: 01 January 1972
Journal of Paleontology (1972) 46 (1): 55–57.
Add to Citation Manager for Biofacies <span class="search-highlight">Analysis</span> of Presence or Absence Data Through <span class="search-highlight">Canonical</span> <span class="search-highlight">Variate</span> <span class="search-highlight">Analysis</span>
Journal Article

Canonical variate analysis of selected benthic foraminifera; a preliminary study of a potential paleobathymetric tool

Randall W. Spencer
Journal: PALAIOS
Published: 01 February 1987
PALAIOS (1987) 2 (1): 91–100.
DOI: https://doi.org/10.2307/3514577
View PDF for article title, <span class="search-highlight">Canonical</span> <span class="search-highlight">variate</span> <span class="search-highlight">analysis</span> of selected benthic foraminifera; a preliminary study of a potential paleobathymetric tool
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Add to Citation Manager for <span class="search-highlight">Canonical</span> <span class="search-highlight">variate</span> <span class="search-highlight">analysis</span> of selected benthic foraminifera; a preliminary study of a potential paleobathymetric tool
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Canonical variate analysis (CVA) biplots for Mockina ex gr. carinata with age as the group classifier. The percentages along each axis label refers to the proportion of variance explained by each eigenvector. Also plotted for each age bin is a centroid representing the mean values of each age bin along both axes, and ellipses representing 2σ from each centroid. Dark blue wireframe models illustrate the extremes of each CV eigenscore still exhibited by natural specimens, overlaid on light blue wireframe models where all CV eigenscores are zero.

Canonical variate analysis (CVA) biplots for Mockina ex gr. carinata wi...

Published: 01 February 2024
Figure 3. Canonical variate analysis (CVA) biplots for Mockina ex gr. carinata with age as the group classifier. The percentages along each axis label refers to the proportion of variance explained by each eigenvector. Also plotted for each age bin is a centroid representing the mean values
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Canonical variate analysis (CVA) biplots for Mockina ex gr. englandi with age as the group classifier. The percentages along each axis label refers to the proportion of variance explained by each eigenvector. Also plotted for each age bin is a centroid representing the mean values of each age bin along both axes, and ellipses representing 2σ from each centroid. Dark blue wireframe models illustrate the extremes of each CV eigenscore still exhibited by natural specimens, overlaid on light blue wireframe models where all CV eigenscores are zero.

Canonical variate analysis (CVA) biplots for Mockina ex gr. englandi wi...

Published: 01 February 2024
Figure 4. Canonical variate analysis (CVA) biplots for Mockina ex gr. englandi with age as the group classifier. The percentages along each axis label refers to the proportion of variance explained by each eigenvector. Also plotted for each age bin is a centroid representing the mean values
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CV 1 eigenscore distribution from canonical variate analysis (CVA) with age as the group classifier of (A) Mockina ex gr. carinata and (B) Mockina ex gr. englandi for specimens of each age bin.

CV 1 eigenscore distribution from canonical variate analysis (CVA) with age...

Published: 01 February 2024
Figure 5. CV 1 eigenscore distribution from canonical variate analysis (CVA) with age as the group classifier of (A) Mockina ex gr. carinata and (B) Mockina ex gr. englandi for specimens of each age bin.
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CV 1 eigenscores from canonical variate analysis (CVA) with age as the group classifier of Mockina ex gr. carinata and Mockina ex gr. englandi across the Kennecott Point section from Carter and Orchard (2007). The Norian/Rhaetian boundary (NRB) is drawn at the base of the Proparvicingula moniliformis Zone. The range of CV 1 eigenscores exclusively exhibited by Rhaetian specimens are highlighted in red for each species. A linear line of best fit is displayed in purple for M. ex gr. carinata, and in green for M. ex gr. englandi, with each regression surrounded by its respective 98% confidence interval.

CV 1 eigenscores from canonical variate analysis (CVA) with age as the grou...

Published: 01 February 2024
Figure 6. CV 1 eigenscores from canonical variate analysis (CVA) with age as the group classifier of Mockina ex gr. carinata and Mockina ex gr. englandi across the Kennecott Point section from Carter and Orchard ( 2007 ). The Norian/Rhaetian boundary (NRB) is drawn at the base
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A, Canonical variate analysis (CVA) plot of the complete inner ear (P+O_All dataset) of all Odontoceti species included in our study (except Basilosauridae, see “Materials and Methods” for explanation). Green square, Platanistoidea; blue triangle, stem Odontoceti; red polygon, Physeteroidea + Ziphiidae; black circle, Delphinida. B, Extreme configurations for each CV axis, red dots represent the positive extreme and green dots the negative extreme configurations. (Color online.)

A, Canonical variate analysis (CVA) plot of the complete inner ear (P+O_All...

Published: 01 November 2021
Figure 5. A, Canonical variate analysis (CVA) plot of the complete inner ear (P+O_All dataset) of all Odontoceti species included in our study (except Basilosauridae, see “Materials and Methods” for explanation). Green square, Platanistoidea; blue triangle, stem Odontoceti; red polygon
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Canonical variate analysis based on shape variations, grouped by facies (1) and stratigraphic position (2), all showing 90% confidence ellipses of population mean. fs = fine silt; GIV-1 = Skaneateles Formation; GIV-2 = Ludlowville Formation; GIV-3 = Moscow Formation; s = silt; m = muddy.

Canonical variate analysis based on shape variations, grouped by facies ( 1...

Published: 01 May 2018
Figure 6 Canonical variate analysis based on shape variations, grouped by facies ( 1 ) and stratigraphic position ( 2 ), all showing 90% confidence ellipses of population mean. fs = fine silt; GIV-1 = Skaneateles Formation; GIV-2 = Ludlowville Formation; GIV-3 = Moscow Formation; s = silt; m
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Graphical result of the canonical variate analysis of hybodont teeth along the first two canonical axes of maximum discrimination in the dataset (Eigenvalue of Axis 1=8.086, which accounted for 74.46% of the variation; Eigenvalue of Axis 2=1.45, which accounted for 13.35% of the variation).

Graphical result of the canonical variate analysis of hybodont teeth along ...

Published: 11 October 2017
Figure 10 Graphical result of the canonical variate analysis of hybodont teeth along the first two canonical axes of maximum discrimination in the dataset (Eigenvalue of Axis 1=8.086, which accounted for 74.46% of the variation; Eigenvalue of Axis 2=1.45, which accounted for 13.35
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Canonical variate analysis showing clear separation of blank-type samples from field samples for AGI soil-gas results.

Canonical variate analysis showing clear separation of blank-type samples f...

Published: 08 August 2017
Fig. 4. Canonical variate analysis showing clear separation of blank-type samples from field samples for AGI soil-gas results.
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Fig. 15. Canonical variate analysis plots comparing teeth of Albertosaurus...

Published: 08 September 2010
Fig. 15. Canonical variate analysis plots comparing teeth of Albertosaurus sarcophagus (this study) with teeth of Gorgosaurus libratus, Daspletosaurus torosus, Daspletosaurus sp. , Tyrannosaurus rex, and unidentified tyrannosaurids from Samman et al. (2005) . The results are similar to those
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Figure 10. Canonical variate analysis of the Caloosa Shell Mercenaria. Percentage of separation on each axis shown in parentheses. Symbols as in Figure 5

Figure 10. Canonical variate analysis of the Caloosa Shell Mercenaria . P...

Published: 01 January 2002
Figure 10. Canonical variate analysis of the Caloosa Shell Mercenaria . Percentage of separation on each axis shown in parentheses. Symbols as in Figure 5
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Multivariate analysis of variance (MANOVA) and canonical variates analysis (CVA) applied to a, low-spired Guembelitria blowi, nov. sp. and middle-spired G. cretacea populations; b, high-spired G. dammula and middle-spired G. cretacea) populations; and c, the entire data set.

Multivariate analysis of variance (MANOVA) and canonical variates analysis ...

Published: 01 April 2010
F igure 6. Multivariate analysis of variance (MANOVA) and canonical variates analysis (CVA) applied to a , low-spired Guembelitria blowi , nov. sp. and middle-spired G. cretacea populations; b , high-spired G. dammula and middle-spired G. cretacea ) populations; and c , the entire data
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Canonical Variates Analysis (CVA) scatter plot performed for the lateral shape analysis.

Canonical Variates Analysis (CVA) scatter plot performed for the lateral sh...

Published: 01 January 2013
Figure 9 Canonical Variates Analysis (CVA) scatter plot performed for the lateral shape analysis.
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Canonical variates analysis (CVA) ordination of malformation type frequencies. The first two CVA axes capture about 82% of the total variance in malformation type frequency data, that is, counts of various malformation types encountered in 600 pollen grains studied in each cone. Only bisaccate pollen–producing taxa were included. Shaded areas indicate convex hulls enveloping data for all five cones per species. For clarity, vectors clarifying abnormality type loading on the CVA axes have been translated away from the origin. Abbreviations: Abi, Abies koreana; Afr, Afrocarpus gracilior; Cat, Cathaya argyrophylla; Ced, Cedrus libani; Ket, Keteleeria evelyniana; Lag, Lagarostrobos franklinii; Man, Manoao colensoi; Nag, Nageia nagi; Phy, Phyllocladus trichomanoides; Pic, Picea orientalis; Pin, Pinus parviflora; Pod, Podocarpus totara; Pru, Prumnopitys andina. NB: this analysis reflects the absolute frequency of malformation types, not the relative abundance of types within the malformation assemblage.

Canonical variates analysis (CVA) ordination of malformation type frequenci...

Published: 01 November 2022
Figure 8. Canonical variates analysis (CVA) ordination of malformation type frequencies. The first two CVA axes capture about 82% of the total variance in malformation type frequency data, that is, counts of various malformation types encountered in 600 pollen grains studied in each cone. Only
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(a, c) Canonical variates analysis (CVA) of mature Acadoparadoxides cranidia; shaded area represents the Assemame paradoxidid assemblage morphospace, and the large cross the holotype of Acadoparadoxides mureroensis. (b, d, e) Thin-plate spline projections of variation along (b) CV1, (d) CV2, (e) CV3 (see Fig. 4a for landmark configuration).

(a, c) Canonical variates analysis (CVA) of mature Acadoparadoxides crani...

Published: 19 June 2017
Figure 8. (a, c) Canonical variates analysis (CVA) of mature Acadoparadoxides cranidia; shaded area represents the Assemame paradoxidid assemblage morphospace, and the large cross the holotype of Acadoparadoxides mureroensis . (b, d, e) Thin-plate spline projections of variation along (b) CV1
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(a, c) Canonical variates analysis (CVA) of mature Acadoparadoxides pygidia; shaded area represents the Assemame paradoxid assamblage morphospace, and the large cross the topotype of Acadoparadoxides mureroensis. (b, d, e) Thin-plate spline projections of variation along (b) CV1, (d) CV2, (e) CV3 (see Fig. 4c for landmark configuration).

(a, c) Canonical variates analysis (CVA) of mature Acadoparadoxides pygid...

Published: 19 June 2017
Figure 11. (a, c) Canonical variates analysis (CVA) of mature Acadoparadoxides pygidia; shaded area represents the Assemame paradoxid assamblage morphospace, and the large cross the topotype of Acadoparadoxides mureroensis . (b, d, e) Thin-plate spline projections of variation along (b) CV1
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Scatter plot of five groups in canonical variates analysis (CVA). mh;0

Scatter plot of five groups in canonical variates analysis (CVA). mh;0

Published: 01 April 2006
Fig. 5. Scatter plot of five groups in canonical variates analysis (CVA). mh;0
Journal Article

Diversity and variation of theropod dinosaur teeth from the uppermost Santonian Milk River Formation (Upper Cretaceous), Alberta: a quantitative method supporting identification of the oldest dinosaur tooth assemblage in Canada

Derek W. Larson
Published: 02 February 2009
Canadian Journal of Earth Sciences (2008) 45 (12): 1455–1468.
DOI: https://doi.org/10.1139/E08-070
... and a canonical variate analysis, provide reasonable separation of all taxa, although better results are achieved by separate analyses based on qualitative observations of denticle shape. The best results of the canonical variate analysis identified 96.0% of specimens correctly. This corroborates the qualitative...
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View PDF for article title, Diversity and <span class="search-highlight">variation</span> of theropod dinosaur teeth from the uppermost Santonian Milk River Formation (Upper Cretaceous), Alberta: a quantitative method supporting identification of the oldest dinosaur tooth assemblage in Canada
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Book Chapter

On stability of compositional canonical variate vector components

Author(s)
R. A. Reyment
Book: Compositional Data Analysis in the Geosciences: From Theory to Practice
Series: Geological Society, London, Special Publications
Publisher: Geological Society of London
Published: 01 January 2006
DOI: 10.1144/GSL.SP.2006.264.01.05
EISBN: 9781862395121
... Abstract Canonical variate analysis (aka discriminant coordinates) is viewed from the aspect of Aitchisonian compositional data analysis and the concept of stability in canonical vectors examined in relation to their refication (i.e. providing canonical vector components with a practical...
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Abstract
View PDF for content titled, On stability of compositional <span class="search-highlight">canonical</span> <span class="search-highlight">variate</span> vector components
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Add to Citation Manager for On stability of compositional <span class="search-highlight">canonical</span> <span class="search-highlight">variate</span> vector components

Abstract Canonical variate analysis (aka discriminant coordinates) is viewed from the aspect of Aitchisonian compositional data analysis and the concept of stability in canonical vectors examined in relation to their refication (i.e. providing canonical vector components with a practical interpretation). The log-ratio transformation was found to have computational and interpretational advantages over the centred log-ratio transformation. The ad hoc application of N. A. Campbell’s application of the method of shrinkage estimators to multiple discrimination, and the optimal retention of discrimination power, is exemplified by two cases, one drawn from quantitative sedimentology, the other from biomolecular palaeontology, with the intention of probing the effect of instability on interpreting the relative importance of standardized canonical variate coefficients in relation to the suppression of near-redundant directions of within-groups variation. Pronounced instability in canonical vectors may endanger the validity of an analysis.