Snv: Difference between revisions
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imported>Jeremy (Importing text file) |
imported>Jeremy (Importing text file) |
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:[xcorr,mns,sds] = snv(x,''options''); %perform snv scaling | :[xcorr,mns,sds] = snv(x,''options''); %perform snv scaling | ||
:x = snv(xcorr,''mns,sds''); %undo snv | :x = snv(xcorr,''mns,sds''); %undo snv | ||
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Scales rows of the input x to be mean zero and unit standard deviation. This is the same as autoscaling the transpose of x. | Scales rows of the input x to be mean zero and unit standard deviation. This is the same as autoscaling the transpose of x. | ||
==== | ====Inputs==== | ||
* '''x''' = ''M'' by ''N'' matrix of data to be scaled (class "double" or "dataset"). | * '''x''' = ''M'' by ''N'' matrix of data to be scaled (class "double" or "dataset"). | ||
==== | ====Optional Inputs==== | ||
* '''options''' = options structure passed to function "auto" when performing SNV scaling. See auto.m for available options (not valid for undo operation). | * '''options''' = options structure passed to function "auto" when performing SNV scaling. See auto.m for available options (not valid for undo operation). | ||
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* '''''sds''''' = vector of length ''M'' of standard deviations. | * '''''sds''''' = vector of length ''M'' of standard deviations. | ||
==== | ====Outputs==== | ||
* '''xcorr''' = the scaled data (xcorr will be the same class as x), | * '''xcorr''' = the scaled data (xcorr will be the same class as x), | ||
Revision as of 16:35, 3 September 2008
Purpose
Standard Normal Variate scaling.
Synopsis
- [xcorr,mns,sds] = snv(x,options); %perform snv scaling
- x = snv(xcorr,mns,sds); %undo snv
Description
Scales rows of the input x to be mean zero and unit standard deviation. This is the same as autoscaling the transpose of x.
Inputs
- x = M by N matrix of data to be scaled (class "double" or "dataset").
Optional Inputs
- options = options structure passed to function "auto" when performing SNV scaling. See auto.m for available options (not valid for undo operation).
- mns = a vector of length M of means, and
- sds = vector of length M of standard deviations.
Outputs
- xcorr = the scaled data (xcorr will be the same class as x),
- mns = vector of means for each row, and
- sds = vector of standard deviations for each row.
To rescale or "undo" SNV, inputs are xcorr, mns, and sds from a previous SNV call. The output will be the original x.