Package index • fmrireg

All functions

ar_parameters(): Extract Estimated AR Parameters from fmri_lm Fit

as.array(<NeuroVec>): Coerce NeuroVec to base array

autoplot(<Reg>): Autoplot method for Reg objects

blockids(<event_model>): Block IDs for event_model

coef(<fmri_meta>): Extract Coefficients from Meta-Analysis

coef_image(): Extract Image/Volume for Coefficient

coef_image(<fmri_ttest_fit>): Extract Coefficient Image from fmri_ttest_fit

columns(): Extract Column Names or Identifiers

conditions(<convolved_term>): Visualize the entire design matrix as a heatmap

contrast(): Contrast generic

contrast(<fmri_meta>): Apply Contrast to Meta-Analysis Results

contrast_set(): Create a contrast set

correlation_map(): correlation_map

correlation_map(<fmri_model>): correlation_map.fmri_model

create_3d_blocks(): Create 3D Blocks for Voxelwise Analysis

create_design_matrix_from_benchmark(): Create Design Matrix from Benchmark Dataset

design_map(<fmri_model>): Heatmap visualization of the combined fmri_model design matrix

design_matrix(<convolved_term>): Design Matrix for Convolved Terms

design_matrix(<fmri_lm>): Design Matrix Method for fmri_lm Objects

design_matrix(<fmri_model>): Design Matrix for fMRI Models

design_plot(): Design Plot for fMRI Model

.resample_param(): Resample parameter vector with specified distribution

estimate(): Deprecated helper: estimate()

estimate_betas(): Estimate Beta Coefficients for fMRI Data

estimate_betas(<fmri_dataset>): Estimate betas using various regression methods

estimate_betas(<matrix_dataset>): Estimate betas for a matrix dataset

estimate_hrf(): Estimate hemodynamic response function (HRF) using Generalized Additive Models (GAMs)

evaluate_method_performance(): Evaluate Method Performance on Benchmark Dataset

event_table(<convolved_term>): Extract event table from convolved term

extract_csv_data(): Extract Data for Meta-Analysis from CSV

fit_contrasts(): Fit Contrasts

fit_contrasts(<default>): Fit Contrasts for Linear Model (Default Method)

fit_contrasts(<fmri_lm>): Fit Contrasts for fMRI Linear Model Objects

fitted_hrf(): fitted_hrf

fitted_hrf(<fmri_lm>): Compute Fitted Hemodynamic Response Functions for an fmri_lm Object

flip_sign(): Flip Sign of Coefficients

fmri_benchmark_datasets: Benchmark fMRI datasets

fmri_latent_lm(): Fast fMRI Regression Model Estimation from a Latent Component Dataset

fmri_lm(): Fit a Linear Regression Model for fMRI Data Analysis

fmri_lm_control(): Configuration for fmri_lm fitting

fmri_meta(): Fit Group-Level Meta-Analysis

fmri_meta_fit(): Fit Meta-Analysis Models

fmri_meta_fit_contrasts(): Fit Meta-Analysis Models with Exact Contrasts

fmri_meta_fit_cov(): Fit Meta-Analysis and return packed covariance per voxel

fmri_meta_fit_extended(): Extended Meta-Analysis Fit with Voxelwise Covariate

fmri_model(): Construct an fMRI Regression Model

fmri_ols_fit(): OLS Fit with Optional Voxelwise Covariate

fmri_rlm(): Fit a Robust Linear Model for fMRI Data Analysis

fmri_ttest(): fmrireg t-tests for Group Analysis

generate_interaction_contrast() generate_main_effect_contrast(): Fast factorial contrast generators

get_benchmark_summary(): Get Benchmark Dataset Summary

get_contrasts(): Get Available Contrasts

get_covariates(): Get Covariates

get_rois(): Get Available ROIs

get_subjects(): Get Subject IDs

glm_lss(): GLM LSS Estimation Convenience Function (Single Trial Estimation)

glm_ols(): GLM OLS Estimation Convenience Function

group_data(): Create Group Dataset for Meta-Analysis

group_data_from_csv(): Create Group Dataset from CSV File or Data Frame

group_data_from_fmrilm(): Create Group Dataset from fmri_lm Objects

group_data_from_h5(): Create Group Dataset from HDF5 Files

group_data_from_nifti(): Create Group Dataset from NIfTI Files

hrf_smoothing_kernel(): Compute an HRF smoothing kernel

list_benchmark_datasets(): List Available Benchmark Datasets

load_benchmark_dataset(): Load fMRI Benchmark Datasets

longnames(): Extract Long Names of Variable Levels

lowrank_control(): Low-rank / sketch controls for fast GLM

meta_effective_n(): Compute Effective Sample Size for Meta-Analysis

meta_fit_vcov_cpp(): Meta-regression with ONE voxelwise covariate

mixed_solve_cpp(): Mixed Model Solver using Rcpp and roptim

n_subjects(): Extract Number of Subjects

ols_t_cpp(): OLS t-test / ANCOVA across features

ols_t_vcov_cpp(): OLS with ONE voxelwise covariate

p_values(): Extract P-values from a Model Fit

paired_diff_block(): Helper Functions for fmri_ttest

print(<fmri_model>) print(<fmri_lm>) print(<fmri_rlm>): Print an fmri_lm_result object

print(<fmri_meta>): Print Meta-Analysis Results

print(<fmri_ttest_fit>): Print method for fmri_ttest_fit

print(<group_data>): Print Group Data Object

print(<spatial_fdr_result>): Print Spatial FDR Results

pvalues(): Compute P-values from Meta-Analysis

r_to_z(): Convert Correlation to Fisher's Z

read_h5_full(): Read All Data from HDF5 Files

read_nifti_full(): Read All Data from NIfTI Files

se(): Extract Standard Errors from Meta-Analysis

shortnames(): Short Names

simulate_bold_signal(): Simulate fMRI Time Series

simulate_fmri_matrix(): Simulate fMRI Time Courses, Return Shared Onsets + Column-Specific Amplitudes/Durations

simulate_noise_vector(): Simulate fMRI Noise

simulate_simple_dataset(): Simulate Complete fMRI Dataset

spatial_fdr(): Spatially-Aware Multiple Comparisons Correction

standard_error(): Extract Standard Errors from a Model Fit

stats(): Extract Test Statistics from a Model Fit

summary(<fmri_meta>): Summary of Meta-Analysis Results

summary(<fmri_ttest_fit>): Summary method for fmri_ttest_fit

summary(<group_data>): Summary of Group Data Object

summary(<spatial_fdr_result>): Summary of Spatial FDR Results

t_to_beta_se(): Convert t-statistics to Effect Sizes

t_to_d(): Convert T-statistics to Effect Sizes and Variances

term_matrices(<fmri_model>): Extract term matrices from fmri_model

tidy(): Tidy generic

tidy(<fmri_meta>): Tidy Meta-Analysis Results

welch_t_cpp(): Welch two-sample t-test across features

write_results(): Write Results from fMRI Analysis

write_results(<fmri_lm>): Write Results from fMRI Linear Model

write_results(<fmri_meta>): Write Meta-Analysis Results

z_to_r(): Back-transform Fisher's Z to Correlation

zscores(): Compute Z-scores from Meta-Analysis