Package com.xinapse.dynamic

Class AutoCorrelationEstimate

java.lang.Object

com.xinapse.dynamic.AutoCorrelationEstimate

public class AutoCorrelationEstimate
extends Object

Class to estimate the auto-correlation of a time-series by examining the residuals of a GLM fit. The auto-correlation is estimated pixel-by-pixel and then a spatial smoothing of the auto-correlation values is applied. The method follows that in: "Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data" Woolrich MW et al NeuroImage 14: 1370-1386 (2001).

Constructor Summary

Constructors

Constructor	Description
AutoCorrelationEstimate(float[][] residuals, int nCols, int nRows, int nSlices, float pixelXSize, float pixelYSize, float pixelZSize, MonitorWorker worker, boolean verbose)	Estimate the auto-correlation for the supplied residuals.

Method Summary

Modifier and Type	Method	Description
float[]	getVarContrasts(List<com.xinapse.dynamic.GLMContrastVector> contrastVectors, int col, int row, int slice, float[][] moorePenrosePsuedoInverse, float[][] moorePenrosePsuedoInverseTranspose, float[][] residualFormingMatrix, double sumSqResiduals)	Get the estimated variances of a set of contrast of Beta (fitted parameter) estimates for a single pixel using this auto-correlation estimate.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

AutoCorrelationEstimate

public AutoCorrelationEstimate(float[][] residuals,
 int nCols,
 int nRows,
 int nSlices,
 float pixelXSize,
 float pixelYSize,
 float pixelZSize,
 MonitorWorker worker,
 boolean verbose)
                        throws CancelledException

Estimate the auto-correlation for the supplied residuals. The auto-correlation can be used for variance correction for estimating the variance of the fitted Beta parameters in a GLM.

Parameters:

residuals - the residuals after fitting using a GLM. The first array index refers to the pixel index, and the second array index refers to the time point.

nCols - number of image columns.

nRows - number of image rows.

nSlices - number of image slices.

pixelXSize - the horizontal pixel size.

pixelYSize - the vertical pixel size.

pixelZSize - the slice spacing.

worker - if non-null, the MonitorWorker that is performing the estimate.

verbose - if verbose reporting to System.out is turned on.

Throws:

CancelledException - if calculation of the auto-correlation is cancelled by the user.

Method Details

getVarContrasts

public float[] getVarContrasts(List<com.xinapse.dynamic.GLMContrastVector> contrastVectors,
 int col,
 int row,
 int slice,
 float[][] moorePenrosePsuedoInverse,
 float[][] moorePenrosePsuedoInverseTranspose,
 float[][] residualFormingMatrix,
 double sumSqResiduals)

Get the estimated variances of a set of contrast of Beta (fitted parameter) estimates for a single pixel using this auto-correlation estimate.

Parameters:

contrastVectors - the set of contrast vectors for which to assess the variances.

col - the column number for the pixel.

row - the row number for the pixel.

slice - the slice umber for the pixel.

moorePenrosePsuedoInverse - the Moore-Penrose pseudo inverse for the GLM design matrix.

moorePenrosePsuedoInverseTranspose - the transpose of the Moore-Penrose pseudo inverse for the GLM design matrix.

residualFormingMatrix - the residual-forming matrix.

sumSqResiduals - the sum of squares of the residuals.

Returns:

a vector of variance estimates for the contrasts in the fitted Beta parameters of the GLM.