AFNI program: 3dWavelets

Program: 3dWavelets 
Author:  B. Douglas Ward 
Initial Release:  28 March 2000 
Latest Revision:  02 December 2002 

Program to perform wavelet analysis of an FMRI 3d+time dataset.        
                                                                       
Usage:                                                                 
3dWavelets                                                             
-type wname          wname = name of wavelet to use for the analysis   
                     At present, there are only two choices for wname: 
                        Haar  -->  Haar wavelets                       
                        Daub  -->  Daubechies wavelets                 
-input fname         fname = filename of 3d+time input dataset         
[-input1D dname]     dname = filename of single (fMRI) .1D time series 
[-mask mname]        mname = filename of 3d mask dataset               
[-nfirst fnum]       fnum = number of first dataset image to use in    
                       the wavelet analysis. (default = 0)             
[-nlast  lnum]       lnum = number of last dataset image to use in     
                       the wavelet analysis. (default = last)          
[-fdisp fval]        Write (to screen) results for those voxels        
                       whose F-statistic is >= fval                    
                                                                       
Filter options:                                                        
[-filt_stop band mintr maxtr] Specify wavelet coefs. to set to zero    
[-filt_base band mintr maxtr] Specify wavelet coefs. for baseline model
[-filt_sgnl band mintr maxtr] Specify wavelet coefs. for signal model  
     where  band  = frequency band                                     
            mintr = min. value for time window (in TR)                 
            maxtr = max. value for time window (in TR)                 
                                                                       
Output options:                                                        
[-coefts cprefix]   cprefix = prefix of 3d+time output dataset which   
                       will contain the forward wavelet transform      
                       coefficients                                    
                                                                       
[-fitts  fprefix]   fprefix = prefix of 3d+time output dataset which   
                       will contain the full model time series fit     
                       to the input data                               
                                                                       
[-sgnlts sprefix]   sprefix = prefix of 3d+time output dataset which   
                       will contain the signal model time series fit   
                       to the input data                               
                                                                       
[-errts  eprefix]   eprefix = prefix of 3d+time output dataset which   
                       will contain the residual error time series     
                       from the full model fit to the input data       
                                                                       
The following options control the contents of the bucket dataset:      
[-fout]            Flag to output the F-statistics                     
[-rout]            Flag to output the R^2 statistics                   
[-cout]            Flag to output the full model wavelet coefficients  
[-vout]            Flag to output the sample variance (MSE) map        
                                                                       
[-stat_first]      Flag to specify that the full model statistics will 
                     appear prior to the wavelet coefficients in the   
                     bucket dataset output                             
                                                                       
[-bucket bprefix]  bprefix = prefix of AFNI 'bucket' dataset containing
                     parameters of interest, such as the F-statistic   
                     for significance of the wavelet signal model.