| BHMSMA | Bayesian hierarchical multi-subject multiscale analysis of functional MRI data |
| BHMSMAfMRI | Bayesian Hierarchical Multi-Subject Multiscale Analysis of Functional MRI Data |
| fmridata | A simulated fMRI data for 3 subjects |
| glmcoeff | Fit GLM to the data time-series and obtain GLM coefficients along with standard error estimates |
| hyperparamest | Get the estimates of the hyperparameters of the BHMSME model along with the estimate of their covariance matrix. |
| pikljbar | Compute the piklj bar values of the BHMSMA model using Newton Cotes algorithm |
| postglmcoeff | Obtain the posterior mean of the GLM coefficients using the posterior mean of the wavelet coefficients. |
| postgroupcoeff | Obtain posterior group coefficients using the BHMSMA methodology. |
| postsamples | Generate samples from the posterior distribution of the GLM coefficients. |
| postwaveletcoeff | Obtain posterior mean and posterior median of the wavelet coefficients using BHMSMA methodology. |
| read.fmridata | Read fMRI data from fMRI image files. |
| waveletcoeff | Apply discrete wavelet transform to the GLM coefficients and obtain the wavelet coefficients. |