Man pages for bbuchsbaum/fmrireg
R package for the anlysis of fmri data
| afni_hrf | construct an native AFNI hrf specification for '3dDeconvolve'... |
| AFNI_HRF-class | AFNI HRF Constructor Function |
| afni_lm | Set up an fMRI linear model for AFNI's 3dDeconvolve |
| afni_trialwise | construct a native AFNI hrf specification for '3dDeconvolve'... |
| amplitudes | Get event amplitudes from an object |
| ar_parameters | Extract Estimated AR Parameters from fmri_lm Fit |
| ar_whiten_inplace | AR(p) whitening of data and design matrices |
| autoplot | Autoplot method for Reg objects |
| baseline | Create a Baseline Specification |
| baseline_model | Construct a Baseline Model |
| baseline_terms | Extract baseline terms from a model |
| basis_suffix | Create Basis Function Suffix |
| block | Create a Block Variable |
| BSpline | B-spline basis |
| build_afni_stims | Build AFNI stimulus definitions |
| cells | The experimental cells of a design |
| chunkwise_lm.fmri_dataset | Perform Chunkwise Linear Modeling on fMRI Dataset |
| chunkwise_lm.fmri_dataset_old | Perform Chunkwise Linear Modeling on fMRI Dataset |
| column_contrast | Column Contrast Specification |
| columns | Extract Column Names or Identifiers |
| condition_basis_list | Convert an 'event_term' to a per-condition basis list |
| conditions | Conditions |
| construct.afni_hrfspec | Construct AFNI HRF specification |
| construct.afni_trialwise_hrfspec | Construct AFNI trialwise HRF specification |
| contrast | Contrast Specification |
| contrast_set | Create a Set of Contrasts |
| contrast_weights | Calculate contrast weights for a given contrast specification... |
| contrast_weights.column_contrast_spec | Column Contrast Weights |
| contrast_weights.contrast_diff_spec | Contrast Difference Weights |
| contrast_weights.contrast_formula_spec | Contrast Formula Weights |
| contrast_weights.contrast_set | Contrast Weights for a Contrast Set |
| contrast_weights.interaction_contrast_spec | Interaction Contrast Weights |
| contrast_weights.oneway_contrast_spec | One-way Contrast Weights |
| contrast_weights.pair_contrast_spec | Pair Contrast Weights |
| contrast_weights.poly_contrast_spec | Polynomial Contrast Weights |
| contrast_weights.unit_contrast_spec | Unit Contrast Weights |
| convolve | Convolve a term with a hemodynamic response function |
| convolve_design | Convolve HRF with Design Matrix. |
| correlation_map | correlation_map |
| correlation_map.baseline_model | correlation_map.baseline_model |
| correlation_map.fmri_model | correlation_map.fmri_model |
| covariate | Construct a Covariate Term |
| create_design_matrix_from_benchmark | Create Design Matrix from Benchmark Dataset |
| create_fmri_model | Create an fmri_model from a Formula |
| design_map | Visualize the entire design matrix as a heatmap |
| design_map.baseline_model | Heatmap visualization of the baseline_model design matrix |
| design_map.fmri_model | Heatmap visualization of the combined fmri_model design... |
| design_matrix | design_matrix |
| design_plot | Design Plot for fMRI Model |
| dot-resample_param | Simulate fMRI Time Courses, Return Shared Onsets +... |
| dot-trial_factor | Internal helper for generating trial factors |
| durations | Get event durations from an object |
| elements | elements |
| 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... |
| evaluate_method_performance | Evaluate Method Performance on Benchmark Dataset |
| event_basis | Create an event set from a ParametricBasis object. |
| event_factor | Create a categorical event sequence from a factor. |
| event_matrix | Create a continuous event set from a matrix. |
| event_model | Construct an event model |
| event_table | Extract event table from a term or model |
| event_term | Create an event model term from a named list of variables. |
| event_terms | Extract event terms from a model |
| event_variable | Create a continuous event sequence from a numeric vector. |
| Fcontrasts | Get block/run indices |
| feature_suffix | Create Feature Suffix |
| 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 |
| fit_lm_contrasts | Fit Linear Model Contrasts |
| fitted_hrf | Evaluate a regressor object over a time grid |
| fitted_hrf.fmri_lm | Extract HRF from Fitted Model |
| fmri_benchmark_datasets | Benchmark fMRI datasets |
| fmri_latent_lm | Fast fMRI Regression Model Estimation from a Latent Component... |
| fmri_lm | Fit a Linear Regression Model for fMRI Data Analysis |
| fmri_lm_control | Configuration for fmri_lm fitting |
| fmri_lm_fit | Fit an fMRI Linear Regression Model with a Specified Fitting... |
| fmri_model | Construct an fMRI Regression Model |
| fmrireg-package | fmrireg: regression tools for fMRI data |
| fmri_rlm | Fit a Robust Linear Model for fMRI Data Analysis |
| gen_afni_lm | generate an AFNI linear model command from a configuration... |
| generate_interaction_contrast | Fast factorial contrast generators |
| get_benchmark_summary | Get Benchmark Dataset Summary |
| get_formula | Model Utilities for fmri_model Objects |
| glm_lss | GLM LSS Estimation Convenience Function (Single Trial... |
| glm_ols | GLM OLS Estimation Convenience Function |
| hrf | hemodynamic regressor specification function for model... |
| hrf_from_coefficients | Combine HRF Basis with Coefficients |
| hrf_smoothing_kernel | Compute an HRF smoothing kernel |
| Ident | Ident |
| interaction_contrast | Interaction Contrast |
| is_categorical | Check if a variable is categorical |
| is_continuous | Check if a variable is continuous |
| labels.event | Get Formatted Labels for a Single Event |
| levels.event | Extract Levels from fmrireg Objects |
| list_benchmark_datasets | List Available Benchmark Datasets |
| load_benchmark_dataset | Load fMRI Benchmark Datasets |
| longnames | Extract Long Names of Variable Levels |
| mixed_solve_cpp | Mixed Model Solver using Rcpp and roptim |
| multiresponse_bootstrap_lm | Multiresponse bootstrap linear model |
| multiresponse_lm | Fit Multiresponse Linear Model |
| nbasis | Return the global onsets of an object |
| neural_input | Generate Neural Input Function from Event Timing |
| nuisance | Create a Nuisance Specification |
| one_against_all_contrast | One Against All Contrast |
| oneway_contrast | One-way Contrast |
| onsets | Return a set of data chunks |
| pair_contrast | Pair Contrast |
| pairwise_contrasts | Pairwise Contrasts |
| penalty_matrix | Generate penalty matrix for regularization |
| plot.baseline_model | Plot a Baseline Model |
| plot_contrasts | plot_contrasts |
| plot_contrasts.event_model | plot_contrasts.event_model |
| Poly | Polynomial basis |
| poly_contrast | Polynomial Contrast |
| predict | Predict from a ParametricBasis object |
| Print a Baseline Model | |
| pull_stat_revised | Extract Statistical Measures from an fmri_lm Object |
| p_values | Extract P-values from a Model Fit |
| reconstruction_matrix | Reconstruction matrix for an HRF basis |
| reexports | Objects exported from other packages |
| regressors | Extract regressor set |
| reshape_coef | Reshape Coefficient Data |
| RobustScale | Robust Scaling (Median/MAD) |
| run.afni_lm_spec | Run an afni_lm_spec object |
| runwise_lm | Perform Runwise Linear Modeling on fMRI Dataset |
| sandwich_variance | Sandwich Variance Estimation in fmrireg |
| sanitize | Sanitize Strings for Use in R Names |
| Scale | Z-score (global) basis |
| ScaleWithin | Z-score within groups |
| shift | Shift a time series object |
| shortnames | Short Names |
| simulate_bold_signal | Simulate fMRI Time Series |
| simulate_noise_vector | Simulate fMRI Noise |
| simulate_simple_dataset | Simulate Complete fMRI Dataset |
| split_by_block | Extract sampling times |
| split_onsets | Split Event Onsets into Lists by Factor Levels or Blocks |
| standard_error | Extract Standard Errors from a Model Fit |
| Standardized | Standardized basis |
| stats | Extract Test Statistics from a Model Fit |
| sub_basis | sub_basis |
| term_indices | Get term indices from a model or term |
| term_matrices | term_matrices |
| to_glt | convert a contrast to an AFNI 'GLT' |
| to_glt.contrast | Convert Contrast to GLT |
| translate_legacy_pattern | Translate legacy contrast regex patterns |
| trialwise | trialwise |
| unit_contrast | Unit Contrast |
| write_glt | Write GLT to File |
