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 |
| as.matrix_dataset | Convert an fMRI Dataset to a Matrix Dataset |
| baseline | Create a Baseline Specification. |
| baseline_model | Construct a Baseline Model. |
| baseline_terms | Extract baseline terms from a model |
| block | Create a Block Variable. |
| blockids | Get block/run indices |
| blocklens | Get block/run lengths |
| BSpline | B-spline basis |
| build_event_model | Build event model from configuration components |
| build_event_model_from_spec | Build Event Model from Specification |
| cells | The experimental cells of a design |
| cells.baseline_model | Retrieve Cells of a Baseline Model. |
| chunkwise_lm.fmri_dataset | Perform Chunkwise Linear Modeling on fMRI Dataset |
| chunkwise_rlm | Perform Chunkwise Robust Linear Modeling on fMRI Dataset |
| coef.fmri_lm | Extract Model Coefficients from an fmri_lm Object |
| compute_best_hrfs | Compute Best HRFs |
| conditions | Conditions |
| conditions.event_term | Extract conditions from an event_term. |
| construct_event_model | Construct Event Model from Convolved Terms |
| construct_event_term_from_spec | Construct Event Term from Regressor Specification |
| construct_model | Construct an Event Model. |
| contrast | Contrast Specification |
| contrast_set | Create a Set of Contrasts |
| contrast_weights | Calculate contrast weights for a given contrast specification... |
| contrast_weights.contrast_diff_spec | Contrast Difference Weights |
| contrast_weights.contrast_formula_spec | Contrast Formula Weights |
| 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_block | Convolve hemodynamic response with a block duration |
| convolve_design | Convolve HRF with Design Matrix. |
| convolve_event_term | Convolve Event Term with HRF |
| convolve.event_term | Convolve an event-related design matrix with an HRF. |
| correlation_map | correlation_map |
| correlation_map.baseline_model | correlation_map.baseline_model |
| correlation_map.event_model | correlation_map.event_model |
| correlation_map.fmri_model | correlation_map.fmri_model |
| covariate | Construct a Covariate Term |
| create_event_model | Create an event model directly from components. |
| create_fmri_model | Create an fMRI Model |
| create_hrf_object | Create HRF Object from Specification |
| create_hrfspec | Create an HRF specification programmatically |
| create_parametric_basis | Create parametric basis from specification |
| create_parametric_basis_expression | create_parametric_basis_expression |
| data_chunks | Return a set of data chunks |
| data_chunks.fmri_mem_dataset | Create Data Chunks for fmri_mem_dataset Objects |
| data_chunks.matrix_dataset | Create Data Chunks for matrix_dataset Objects |
| design_map.baseline_model | Heatmap visualization of the baseline_model design matrix |
| design_map.event_model | Visualize the entire design matrix of an event_model as a... |
| design_map.fmri_model | Heatmap visualization of the combined fmri_model design... |
| design_matrix | design_matrix |
| design_matrix.baseline_model | Construct a Design Matrix for a Baseline Model. |
| design_matrix.event_term | Construct a design matrix for an event_term. |
| design_plot | Design Plot for fMRI Model |
| despike | Despike Time Series Data |
| dot-all_symbols_in_call | Recursively find all symbol names used inside a... |
| dot-checkEVArgs | Validate event arguments. |
| dot-correlation_map_common | Internal helper to build a correlation heatmap from a numeric... |
| dot-extract_expr_variables_into_events | Detect variables inside exprs(...) calls and copy those... |
| dot-sanitizeName | Sanitize a variable name. |
| durations | Get event durations from an object |
| elements | elements |
| estimate_betas | Estimate Beta Coefficients for fMRI Data |
| estimate_betas.fmri_dataset | Estimate betas using the Rank-1 GLM methods (R1 and R1-GLMS... |
| estimate_betas.matrix_dataset | Estimate betas for a matrix dataset |
| estimate_hrf | Estimate hemodynamic response function (HRF) using... |
| estimate_r1 | keywords internal |
| estimate_r1_glms | Estimate betas using Rank-1 GLM with separate designs... |
| EV | EV |
| evaluate | Evaluate a regressor object over a time grid |
| evaluate.HRF | evaluate.HRF |
| evaluate.single_trial_regressor | Evaluate a single trial regressor |
| 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_model.formula | event_model.formula |
| event_model.list | event_model.list |
| 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 | Generate F-contrasts for a model term |
| Fcontrasts.event_term | Compute F-contrasts for an event_term. |
| find_best_hrf | Generic S3 method for 'find_best_hrf' |
| find_best_hrf.fmri_mem_dataset | find_best_hrf for fmri_mem_dataset |
| find_best_hrf.matrix_dataset | find_best_hrf for a matrix_dataset |
| fit_lm_contrasts | Fit Linear Model Contrasts |
| fitted_hrf | fitted_hrf |
| fitted_hrf.fmri_lm | Compute Fitted Hemodynamic Response Functions for an fmri_lm... |
| fmri_dataset | Create an fMRI Dataset Object from a Set of Scans |
| FMRIGroupDataset | R6 Class for Managing Multi-Subject 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_fit | Fit an fMRI Linear Regression Model with a Specified Fitting... |
| fmri_mem_dataset | Create an fMRI Memory Dataset Object |
| 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 |
| formula.event_term | Build a formula for an event term. |
| fracridge | Fractional Ridge Regression |
| fracridge_cv | Fractional Ridge Regression with Cross-Validation |
| gen_afni_lm | generate an AFNI linear model command from a configuration... |
| gen_empirical_hrf | Generate an Empirical Hemodynamic Response Function |
| gen_hrf | Construct an HRF Instance |
| gen_hrf_blocked | Generate a Blocked HRF Function |
| gen_hrf_lagged | Generate a Lagged HRF Function |
| gen_hrf_set | Generate an HRF Basis Set |
| get_formula.fmri_model | Get the formula representation of an fMRI model |
| get_scan_length | Get run length for a specific scan |
| get_scan_tr | Get TR for a specific scan |
| global_onsets | Return the global onsets of an object |
| global_onsets.sampling_frame | Compute global onsets from a sampling_frame |
| grapes-or-or-grapes | The %||% operator |
| hrf | hemodynamic regressor specification function for model... |
| hrf_bspline | B-spline HRF (hemodynamic response function) |
| HRF-class | HRF Constructor Function |
| HRF_DAGUERRE | Daguerre HRF |
| HRF_DAGUERRE_BASIS | Create Daguerre basis HRF set |
| hrf_gamma | Gamma HRF (hemodynamic response function) |
| hrf_gaussian | Gaussian HRF (hemodynamic response function) |
| hrf_half_cosine | Hemodynamic Response Function with Half-Cosine Basis |
| hrf_inv_logit | hrf_inv_logit |
| hrf_mexhat | Mexican Hat HRF (hemodynamic response function) |
| hrf_sine | hrf_sine |
| hrf_smoothing_kernel | Compute an HRF smoothing kernel |
| hrf_spmg1 | hrf_spmg1 |
| hrf_time | HRF (hemodynamic response function) as a linear function of... |
| hrf_toeplitz | HRF Toeplitz Matrix |
| Ident | Ident |
| instantaneous_correlation | Compute Instantaneous Correlation between Two Signals |
| instantaneous_correlation_rcpp | Compute Instantaneous Correlation between Two Signals (Rcpp... |
| interaction_contrast | Interaction Contrast |
| is_categorical | Check if a variable is categorical |
| is_continuous | Check if a variable is continuous |
| is.increasing | Check if a vector is non-decreasing. |
| is.strictly.increasing | Check if a vector is strictly increasing. |
| latent_dataset | Create a Latent Dataset Object |
| levels | levels |
| load_fmri_config | Load and validate fMRI analysis configuration |
| longnames | extract long names of variable |
| matrix_dataset | Create a Matrix Dataset Object |
| matrix_term | matrix_term |
| 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 number of basis functions associated with HRF |
| neural_input | Generate Neural Input Function from Event Timing |
| new_best_hrf_result | Create a new "best_hrf_result" object |
| nuisance | Create a Nuisance Specification. |
| one_against_all_contrast | One Against All Contrast |
| oneway_contrast | One-way Contrast |
| onsets | Get event onsets from an object |
| pair_contrast | Pair Contrast |
| pairwise_contrasts | Pairwise Contrasts |
| plot.baseline_model | Plot a Baseline Model. |
| plot_contrasts.event_model | plot_contrasts.event_model |
| plot.event_model | Plot an event_model object |
| plot.regressor | plot a regressor object |
| Poly | Polynomial basis |
| poly_contrast | Polynomial Contrast |
| predict.fracridge | Predict Method for fracridge Objects |
| prediction_matrix | (Internal) Prediction Matrix |
| print.afni_hrf_convolved_term | Print afni_hrf_convolved_term objects. |
| print.baseline_model | Print a Baseline Model. |
| print.best_hrf_result | Print method for "best_hrf_result" |
| print.BSplineHRF | Print method for B-spline HRF objects |
| print.chunkiter | Pretty Print a Chunk Iterator |
| print.contrast | Print Contrast |
| print.contrast_diff_spec | Print Contrast Difference Specification |
| print.contrast_set | Print Contrast Set |
| print.contrast_spec | Print Contrast Specification |
| print.convolved_term | Print convolved_term objects. |
| print.data_chunk | Pretty Print a Data Chunk Object |
| print.event_factor | Print event_factor objects. |
| print.event_matrix | Print event_matrix objects. |
| print.event_term | Print event_term objects. |
| print.event_variable | Print event_variable objects. |
| print.fmri_lm | Print an fmri_lm_result object |
| print.fmri_rlm | Print method for fmri_rlm objects |
| print.fmri_term | Print fmri_term objects. |
| print.fracridge | Print Method for fracridge Objects |
| print.fracridge_cv | Print Method for fracridge_cv Objects |
| print.GaussianHRF | Print method for Gaussian HRF objects |
| print.HRF | Print method for HRF objects |
| print.poly_contrast_spec | Print Polynomial Contrast Specification |
| print.SPMGHRF | Print method for SPMG HRF objects |
| pull_stat | Extract Statistical Measures from an fmri_lm Object |
| p_values | Extract P-values from a Model Fit |
| r1_glm_betas | Rank-1 GLM Solver |
| read_fmri_config | read a basic fMRI configuration file |
| regressor | construct a regressor object |
| regressors | Extract regressor set |
| rescale_columns_01_to_neg1_pos1 | Rescale columns of a design matrix to (-1,1). |
| reshape_coef | Reshape Coefficient Data |
| run.afni_lm_spec | Run an afni_lm_spec object |
| runwise_lm | Perform Runwise Linear Modeling on fMRI Dataset |
| runwise_rlm | Perform Runwise Robust Linear Modeling on fMRI Dataset |
| samples | Extract sampling times |
| samples.sampling_frame | Extract samples from a sampling_frame |
| sampling_frame | Construct a sampling_frame |
| setup_hrf_library | Setup an HRF Library |
| shift | Shift a time series object |
| shift.regressor | Shift method for the regressor class |
| shortnames | extract short names of variable |
| sim_ts | Simulate fMRI Time Series |
| simulate_fmri_dataset | Simulate Complete fMRI Dataset |
| simulate_fmri_noise | Simulate fMRI Noise |
| single_trial_regressor | Create a single trial regressor |
| smooth_hrf_assignments | Smooth HRF Assignments |
| split_by_block | Split variables by block ID |
| split_onsets | Split Event Onsets into Lists by Factor Levels or Blocks |
| split_onsets.event_term | Split onsets of an event_term object. |
| standard_error | Extract Standard Errors from a Model Fit |
| standard_error.fmri_latent_lm | Calculate the standard error for an fmri_latent_lm object |
| standard_error.fmri_lm | Extract Standard Errors from an fmri_lm Object |
| Standardized | Standardized basis |
| stats | Extract Test Statistics from a Model Fit |
| stats.fmri_lm | Extract Statistical Values from an fmri_lm Object |
| sub_basis | sub_basis |
| term_indices | Get term indices from a model or term |
| term_matrices.fmri_model | Extract Term Matrices from an fMRI Model |
| terms.baseline_model | Return the Terms of a Baseline Model. |
| to_glt | convert a contrast to an AFNI 'GLT' |
| to_glt.contrast | Convert Contrast to GLT |
| trialwise | trialwise |
| unit_contrast | Unit Contrast |
| unpack_chunkwise | Unpack Chunkwise Results |
| validate_hrf_params | Validate HRF parameters |
| vec_len | Calculate Vector Length |
| write_glt.glt_contrast | Write GLT to File |
