| BayesfMRI-package | BayesfMRI: Spatial Bayesian Methods for Task Functional MRI Studies | 
| .findTheta | Perform the EM algorithm of the Bayesian GLM fitting | 
| .getSqrtInvCpp | Get the prewhitening matrix for a single data location | 
| .initialKP | Find the initial values of kappa2 and phi | 
| .logDetQt | Find the log of the determinant of Q_tilde | 
| activations | Identify field activations | 
| aic_Param | aic | 
| ar_order_Param | ar_order | 
| ar_smooth_Param | ar_smooth | 
| BayesfMRI | BayesfMRI: Spatial Bayesian Methods for Task Functional MRI Studies | 
| BayesGLM | BayesGLM for CIFTI | 
| BayesGLM2 | Group-level Bayesian GLM | 
| Bayes_Param | Bayes | 
| BOLD_Param_BayesGLM | BOLD | 
| brainstructures_Param_BayesGLM | brainstructures | 
| buffer_Param | buffer | 
| Connectome_Workbench_Description | Connectome Workbench | 
| contrasts_Param | contrasts | 
| design_Param_BayesGLM | design | 
| do_QC | Mask out invalid data | 
| emTol_Param | emTol | 
| EM_Param | EM | 
| faces_Param | faces | 
| field_names_Param | field_names | 
| fit_bayesglm | fit_bayesglm | 
| hpf_Param_BayesGLM | hpf | 
| id_activations | Identify field activations | 
| INLA_Description | INLA | 
| INLA_Latent_Fields_Limit_Description | INLA Latent Fields | 
| make_mesh | Make Mesh | 
| mask_Param_vertices | mask: vertices | 
| max_threads_Param | max_threads | 
| mean_var_Tol_Param | mean and variance tolerance | 
| mesh_Param_either | mesh: either | 
| mesh_Param_inla | mesh: INLA only | 
| nbhd_order_Param | nbhd_order | 
| nuisance_Param_BayesGLM | nuisance | 
| n_threads_Param | n_threads | 
| plot.act_BGLM | S3 method: use 'view_xifti' to plot a '"act_BGLM"' object | 
| plot.BGLM | S3 method: use 'view_xifti' to plot a '"BGLM"' object | 
| plot.BGLM2 | S3 method: use 'view_xifti' to plot a '"BGLM2"' object | 
| plot.prev_BGLM | S3 method: use 'view_xifti' to plot a '"prev_BGLM"' object | 
| prevalence | Activations prevalence. | 
| print.act_BGLM | Summarize a '"act_BGLM"' object | 
| print.act_fit_bglm | Summarize a '"act_fit_bglm"' object | 
| print.BGLM | Summarize a '"BGLM"' object | 
| print.BGLM2 | Summarize a '"BGLM2"' object | 
| print.fit_bglm | Summarize a '"fit_bglm"' object | 
| print.fit_bglm2 | Summarize a '"fit_bglm2"' object | 
| print.prev_BGLM | Summarize a '"prev_BGLM"' object | 
| print.prev_fit_bglm | Summarize a '"prev_fit_bglm"' object | 
| print.summary.act_BGLM | Summarize a '"act_BGLM"' object | 
| print.summary.act_fit_bglm | Summarize a '"act_fit_bglm"' object | 
| print.summary.BGLM | Summarize a '"BGLM"' object | 
| print.summary.BGLM2 | Summarize a '"BGLM2"' object | 
| print.summary.fit_bglm | Summarize a '"fit_bglm"' object | 
| print.summary.fit_bglm2 | Summarize a '"fit_bglm2"' object | 
| print.summary.prev_BGLM | Summarize a '"prev_BGLM"' object | 
| print.summary.prev_fit_bglm | Summarize a '"prev_fit_bglm"' object | 
| resamp_res_Param_BayesGLM | resamp_res | 
| return_INLA_Param | return_INLA | 
| scale_BOLD | Scale the BOLD timeseries | 
| scale_BOLD_Param | scale_BOLD | 
| scrub_Param_BayesGLM | scrub | 
| seed_Param | seed | 
| session_names_Param | session_names | 
| summary.act_BGLM | Summarize a '"act_BGLM"' object | 
| summary.act_fit_bglm | Summarize a '"act_fit_bglm"' object | 
| summary.BGLM | Summarize a '"BGLM"' object | 
| summary.BGLM2 | Summarize a '"BGLM2"' object | 
| summary.fit_bglm | Summarize a '"fit_bglm"' object | 
| summary.fit_bglm2 | Summarize a '"fit_bglm2"' object | 
| summary.prev_BGLM | Summarize a '"prev_BGLM"' object | 
| summary.prev_fit_bglm | Summarize a '"prev_fit_bglm"' object | 
| surfaces_Param_BayesGLM | surfaces | 
| trim_INLA_Param | trim_INLA | 
| TR_Param_BayesGLM | TR | 
| verbose_Param | verbose | 
| vertex_areas | Surface area of each vertex | 
| vertices_Param | vertices | 
| vol2spde | Construct a triangular mesh from a 3D volumetric mask |