<p>A bi-dimensional plotting of the principal component analysis using the five acoustic variables (PF, Q1, Q2, Q3, pureness) on spectrograms of cicada calling songs at the SP mountain site of Taiwan.</p
<p>Combined effects of the three sound parameters (pulse length, frequency, and intensity) shown as ...
<p>Axis 1 (horizontal) = 94.0% of variance explained, axis 2 (vertical) = 6.0%. Acronyms of the thre...
<p>The first two principal component axes are displayed. Sites are coded according to: (a) the areal...
<p>Depicted are the Eigenvectors of the first and second principal components of 15 acoustic variabl...
<p>Principal components analysis of measurements of song characters for Asian <i>Muscicapa</i> taxa....
<p>A. Relative contributions of different acoustic parameters to PCA eigenvectors; the darkness of t...
Specific identification of three Tibicen cicadas, T. japonicus, T. flammatus and T. bihamatus, by th...
CBV = Cerro Buena Vista, CV = Cerro Vueltas, CCH = Cerro Chirripó, IV = Irazú Volcano.</p
<p>(a) Two-dimensional plot of the first two factors extracted by principal components analysis over...
Factor scores extracted using PCA, summarizing variation in fine structural characteristics of all s...
<p>Principal Component Analysis Bi-plot graph. Each dot represents an animal in the study and triang...
<p>PCA plot of the environmental conditions in the study area based on 15 variables and altitude use...
Plots of factor scores of principal component analysis of three populations of Corydoras undulatus. ...
Attention is drawn to some useful but not generally known properties of principal components analysi...
<p>Larger values on PC1 represent songs that are longer, that have more notes (that are shorter) and...
<p>Combined effects of the three sound parameters (pulse length, frequency, and intensity) shown as ...
<p>Axis 1 (horizontal) = 94.0% of variance explained, axis 2 (vertical) = 6.0%. Acronyms of the thre...
<p>The first two principal component axes are displayed. Sites are coded according to: (a) the areal...
<p>Depicted are the Eigenvectors of the first and second principal components of 15 acoustic variabl...
<p>Principal components analysis of measurements of song characters for Asian <i>Muscicapa</i> taxa....
<p>A. Relative contributions of different acoustic parameters to PCA eigenvectors; the darkness of t...
Specific identification of three Tibicen cicadas, T. japonicus, T. flammatus and T. bihamatus, by th...
CBV = Cerro Buena Vista, CV = Cerro Vueltas, CCH = Cerro Chirripó, IV = Irazú Volcano.</p
<p>(a) Two-dimensional plot of the first two factors extracted by principal components analysis over...
Factor scores extracted using PCA, summarizing variation in fine structural characteristics of all s...
<p>Principal Component Analysis Bi-plot graph. Each dot represents an animal in the study and triang...
<p>PCA plot of the environmental conditions in the study area based on 15 variables and altitude use...
Plots of factor scores of principal component analysis of three populations of Corydoras undulatus. ...
Attention is drawn to some useful but not generally known properties of principal components analysi...
<p>Larger values on PC1 represent songs that are longer, that have more notes (that are shorter) and...
<p>Combined effects of the three sound parameters (pulse length, frequency, and intensity) shown as ...
<p>Axis 1 (horizontal) = 94.0% of variance explained, axis 2 (vertical) = 6.0%. Acronyms of the thre...
<p>The first two principal component axes are displayed. Sites are coded according to: (a) the areal...