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===Purpose=== | ===Purpose=== | ||
Standard Normal Variate scaling. | Standard Normal Variate scaling. | ||
===Synopsis=== | ===Synopsis=== | ||
:[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 | ||
===Description=== | ===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. | |||
==== | Scales rows of the input <tt>x</tt> to be mean zero and unit standard deviation. This is the same as autoscaling the transpose of <tt>x</tt>. | ||
====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). | ||
* '''''mns''''' = a vector of length ''M'' of means, and | * '''''mns''''' = a vector of length ''M'' of means, and | ||
* '''''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), | ||
* '''mns''' = vector of means for each row, and | * '''mns''' = vector of means for each row, and | ||
* '''sds''' = vector of standard deviations for each row. | * '''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. | To rescale or "undo" SNV, inputs are xcorr, mns, and sds from a previous SNV call. The output will be the original x. | ||
===See Also=== | ===See Also=== | ||
[[auto]], [[normaliz]], [[preprocess]] | [[auto]], [[normaliz]], [[preprocess]] | ||
Latest revision as of 12:35, 9 October 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.