Varcapy: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
Calculate percent y-block variance captured by a PLS regression model. | Calculate percent y-block variance captured by a PLS regression model. | ||
===Synopsis=== | ===Synopsis=== | ||
:vc = varcapy(model'',options'') | :vc = varcapy(model'',options'') | ||
===Description=== | ===Description=== | ||
VARCAPY Calculate percent y-block variance captured by a PLS regression model. Given a PLS regression model, VARCAPY calculates the percent of y-block variance captured by each latent variable of the model for each column of the y-block. | VARCAPY Calculate percent y-block variance captured by a PLS regression model. Given a PLS regression model, VARCAPY calculates the percent of y-block variance captured by each latent variable of the model for each column of the y-block. | ||
Input is a standard PLS model structure. Outupt is a matrix containing the variance captured by each latent variable (rows) for each column of y (columns). | |||
Input is a standard PLS model structure, <tt>model</tt> and an optional options structure (see options below). Outupt, <tt>vc</tt>, is a matrix containing the variance captured by each latent variable (rows) for each column of y (columns). | |||
===Options=== | ===Options=== | ||
* plots : [ 'none' |{'final'}] Governs plotting of results. | |||
* '''plots''' : [ 'none' |{'final'}] Governs plotting of results. | |||
===See Also=== | ===See Also=== | ||
[[analysis]], [[pca]] | [[analysis]], [[pca]] | ||
Latest revision as of 10:00, 10 October 2008
Purpose
Calculate percent y-block variance captured by a PLS regression model.
Synopsis
- vc = varcapy(model,options)
Description
VARCAPY Calculate percent y-block variance captured by a PLS regression model. Given a PLS regression model, VARCAPY calculates the percent of y-block variance captured by each latent variable of the model for each column of the y-block.
Input is a standard PLS model structure, model and an optional options structure (see options below). Outupt, vc, is a matrix containing the variance captured by each latent variable (rows) for each column of y (columns).
Options
- plots : [ 'none' |{'final'}] Governs plotting of results.