<p>For each discriminative components obtained from heteroscedastic linear discriminant function analysis, both the loadings of morphological variables and Pearson correlation coefficients are shown (the latter in brackets; significant correlations in boldface). *Dark chevron blotches on fish sides were indexed as 0; unclear/no dark patterns were indexed as 1.</p
<p>The standardized coefficients in bold indicate the factors from the factor analysis that contribu...
<p>Number of variables in model: 10; grouping - 3 groups. Wilks's lambda coefficient – 0.045; F-test...
Significant (red and green) and non-significant (yellow) discriminant taxonomic nodes are colored. C...
<p>Coefficients of the linear discriminant function of ecomorphology for each variable examined.</p
<p>Includes 31 AT (•) and 31 AZ (▴) used as training dataset for heteroscedastic linear discriminant...
<p>Discriminant function analysis based on duration, source (F0) and filter (formants) variables. Th...
<p>Discriminant functions DF1 and DF2 account for 65.7% and 32.0% of the total variance, respectivel...
Discriminant function analysis on traditional characters among five fish species (100.0% of original...
Discriminant function analysis on truss characters among five fish species (96.1% of original groupe...
<p>Correlation coefficient between original variables and the scores of the discriminant functions o...
<p>LDA produced an axis of variation that effectively separated non-sifters (top panel) from special...
(Group Centroids: 1: P. chola; 2: P. conchonius; 3: S. sarana; 4: P. sophore 5: P. ticto).</p
The technique of discriminant function analysis was originated by R.A. Fisher and first applied by B...
<p>The results of the discriminant function analysis on experimental assemblage showing the loadings...
In bold, characters with the greatest weight in DF1. For explanation of morphological characters, se...
<p>The standardized coefficients in bold indicate the factors from the factor analysis that contribu...
<p>Number of variables in model: 10; grouping - 3 groups. Wilks's lambda coefficient – 0.045; F-test...
Significant (red and green) and non-significant (yellow) discriminant taxonomic nodes are colored. C...
<p>Coefficients of the linear discriminant function of ecomorphology for each variable examined.</p
<p>Includes 31 AT (•) and 31 AZ (▴) used as training dataset for heteroscedastic linear discriminant...
<p>Discriminant function analysis based on duration, source (F0) and filter (formants) variables. Th...
<p>Discriminant functions DF1 and DF2 account for 65.7% and 32.0% of the total variance, respectivel...
Discriminant function analysis on traditional characters among five fish species (100.0% of original...
Discriminant function analysis on truss characters among five fish species (96.1% of original groupe...
<p>Correlation coefficient between original variables and the scores of the discriminant functions o...
<p>LDA produced an axis of variation that effectively separated non-sifters (top panel) from special...
(Group Centroids: 1: P. chola; 2: P. conchonius; 3: S. sarana; 4: P. sophore 5: P. ticto).</p
The technique of discriminant function analysis was originated by R.A. Fisher and first applied by B...
<p>The results of the discriminant function analysis on experimental assemblage showing the loadings...
In bold, characters with the greatest weight in DF1. For explanation of morphological characters, se...
<p>The standardized coefficients in bold indicate the factors from the factor analysis that contribu...
<p>Number of variables in model: 10; grouping - 3 groups. Wilks's lambda coefficient – 0.045; F-test...
Significant (red and green) and non-significant (yellow) discriminant taxonomic nodes are colored. C...