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<html><head><title>pca</title></head><body bgcolor=white><h1 align=center>Description of the program: <font color=Blue>pca</font></h1><hr>This program performs a global principal component analysis (PCA). Itgives the eigenvalues of the covariance matrix and depending on the<font color=red>-W</font> flag eigenvectors, projections... of theinput time series.<hr><h2 align=center>Usage:</h2><center><font color=Red>pca [Options]</font><p>Everything not being a valid option will be interpreted as a potential datafile name. Given no datafile at all, means read stdin. Also <font color=Red>-</font> means stdin<p>Possible options are:<p><table border=2><tr><th>Option<th>Description<th>Default</tr><tr><th>-l#<td>number of data to be used<td>whole file</tr><tr><th>-x#<td>number of lines to be ignored<td>0</tr><tr><th>-c#<td><a href=../general.html#column>columns to be read</a><td>1</tr><tr><th>-m#,#<td>no. of input columns,embedding dimension<td>2,1</tr><tr><th>-d#<td>delay<td>1</tr><tr><th>-W#<td><b>0:</b> Just write the eigenvalues<br><b>1:</b> Write the eigenvectors. The columns of the output matrix are theeigenvectors.<br><b>2:</b> Transformation of the time series onto the eigenvector basis. Thenumber of components printed is determined by the <fontcolor=red>-q</font> flag.<br><b>3:</b> Project the time series onto the first <fontcolor=red>-q</font> eigenvectors (global noise reduction).<td>0</tr><tr><th>-q#<td>depending on <font color=red>-W</font>:<br><b><font color=red>-W2</font>:</b> Number of components written<br><b><font color=red>-W3</font>:</b> Projection dimension<td>full dimension</tr><tr><th>-o[#]<td><a href=../general.html#outfile>output file name</a><td>-o without argument means 'datafile'.pca<br>(or stdin.pca if data were read from stdin)<br>without -o means stdout</tr><tr><th>-V#<td><a href=../general.html#verbosity>verbosity level</a><br> 0: only panic messages<br> 1: add input/output messages<td>1</tr><tr><th>-h<td>show these options<td>none</tr></table></center><hr><h2 align=center>Description of the Output:</h2>The output consists of the eigenvalues and depending on the <fontcolor=blue>-W</font> flag of the eigenvectors, the new components orthe projected time series.<hr>View the <a href="../../source_c/pca.c"> C-sources</a>.<hr><a href=../contents.html>Table of Contents</a> * <a href="../../index.html" target="_top">TISEAN home</a></body></html>⌨️ 快捷键说明
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