| 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 |