Man pages for bbuchsbaum/fmrireg
R package for the anlysis of fmri data
| afni_hrf | construct an native AFNI hrf specification for '3dDeconvolve'... |
| afni_lm | Set up an fMRI linear model for AFNI's 3dDeconvolve |
| afni_trialwise | construct an native AFNI hrf specification for '3dDeconvolve'... |
| amplitudes | get amplitude vector |
| baseline | Create a model specification for modeling low-frequency drift... |
| baseline_model | construct a baseline model to model noise and other... |
| baseline_term | baseline_term |
| baseline_terms | baseline_terms |
| beta_stats | Beta Statistics for Linear Model |
| block | a block variable, which is constant over the span of a... |
| blockids | get the block indices |
| blocklens | get block lengths |
| block_term | block_term |
| BSpline | B-spline basis |
| build_afni_stims | generate a set of AFNI stimuli for '3dDeconvolve' |
| build_decon_command | Build 3dDeconvolve command for an fMRI model |
| cells | The experimental cells of a design |
| chunkwise_lm | estimate a linear model sequentially for each "chunk" (a... |
| chunkwise_lm.fmri_dataset | Chunkwise Linear Model for fMRI Dataset |
| chunkwise_lm.latent_dataset | Internal function for performing chunkwise linear regression... |
| columns | columns |
| conditions | Conditions |
| conform_len | check vector is of length 1 or repeated for supplied length |
| construct | construct |
| contrast | Contrast Specification |
| contrast_set | Create a Set of Contrasts |
| contrast_weights | contrast_weights |
| contrast_weights.poly_contrast_spec | Polynomial Contrast Weights |
| contrast_weights.unit_contrast_spec | Unit Contrast Weights |
| convolve | convolve |
| convolve_block | Convolve hemodynamic response with a block duration |
| convolve_design | Convolve HRF with Design Matrix |
| convolve.event_term | Convolve an event-related design matrix with an HRF. |
| covariate | Construct a Covariate Term |
| data_chunks | return a set of data chunks |
| data_chunks.fmri_file_dataset | Create Data Chunks for fmri_file_dataset Objects |
| 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_env | design_env |
| design_matrix | design_matrix |
| design_plot | Design Plot for fMRI Model |
| despike | Despike Time Series Data |
| durations | get event durations of a variable |
| elements | elements |
| estcon | estcon |
| estimate_betas | estimate trialwise beta coefficients for a dataset |
| estimate_betas.fmri_dataset | #' @export estimate_betas.fmri_mem_dataset <-... |
| estimate_betas.matrix_dataset | Estimate betas for a matrix dataset |
| estimate_hrf | Estimate hemodynamic response function (HRF) using... |
| evaluate | evaluate a function over a sampling grid |
| evaluate.HRF | evaluate.HRF |
| evaluate.hrfspec | evaluate.hrfspec |
| 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 valued 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 | event_table |
| event_term | Create an event model term from a named list of variables. |
| event_terms | event_terms |
| event_variable | Create a continuous valued event sequence from a numeric... |
| Fcontrasts | Fcontrasts |
| Fcontrasts.event_term | Compute F-contrasts for Event Term |
| fit_contrasts | Fit Contrasts for Linear Model |
| fit_Fcontrasts | Fit F-contrasts for Linear Model |
| fmri_dataset | Create an fMRI Dataset Object from a Set of Scans |
| 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 | fmrireg: regresssion tools for fMRI data |
| fmri_rlm | fmri_rlm |
| gen_afni_lm | generate an AFNI linear model command from a configuration... |
| gen_afni_lm.fmri_config | Generate an AFNI Linear Model from an fmri_config object |
| 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_library | Generate an HRF (hemodynamic response function) library |
| gen_hrf_set | Generate an HRF Basis Set |
| get_data | get_data |
| get_formula | get_formula |
| getHRF | getHRF |
| get_mask | get_mask |
| global_onsets | return the "global" onsets of an object. |
| global_onsets.sampling_frame | Compute global onsets from a sampling_frame |
| hrf | hemodynamic regressor specification function for model... |
| hrf_bspline | B-spline HRF (hemodynamic response function) |
| HRF-class | AFNI HRF Constructor Function |
| 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 |
| is_categorical | is_categorical |
| is_continuous | is_continuous |
| latent_dataset | Create a Latent Dataset Object |
| levels | levels |
| longnames | extract long names of variable |
| matrix_dataset | Create a Matrix Dataset Object |
| matrix_term | matrix_term |
| meta_contrasts | Meta-analysis of contrasts |
| meta_Fcontrasts | Meta-analysis of F-contrasts |
| meta_fixef | Fixed-effects meta-analysis |
| meta_stouffer | Meta-analysis using Stouffer's method |
| multiresponse_arma | Fit a multiresponse ARMA model |
| multiresponse_bootstrap_lm | Multiresponse Bootstrap Linear Model |
| multiresponse_lm | Multiresponse Linear Model |
| nbasis | return number of basis functions associated with hrf. |
| nuisance | nuisance |
| null_regressor | null_regressor |
| one_against_all_contrast | One Against All Contrast |
| onsets | get event onsets of a variable |
| pair_contrast | Pair Contrast |
| pairwise_contrasts | Pairwise Contrasts |
| parent_terms | parent_terms |
| plot.event_model | Plot an event_model object |
| plot.regressor | plot a regressor object |
| Poly | Polynomila basis |
| poly_contrast | Polynomial Contrast |
| print.fmri_betas | Pretty print method for fmri_betas objects |
| p_values | p_values |
| read_fmri_config | read a basic fMRI configuration file |
| regressor | construct a regressor object |
| run | run |
| run.afni_lm_spec | Run an afni_lm_spec object |
| runwise_lm | Runwise Linear Model for fMRI Dataset |
| samples | extract samples |
| samples.sampling_frame | Extract samples from a sampling_frame |
| sampling_frame | Construct a sampling_frame |
| shift | Shift a time series object |
| shortnames | extract short shortnames of variable |
| sim_ts | Simulate fMRI Time Series |
| simulate_fmri_noise | Simulate fMRI Noise using ARMA Model |
| single_trial_regressor | single_trial_regressor |
| soft_threshold | Soft-threshold function |
| split_by_block | split_by_block |
| split_onsets | split an onset vector into a list |
| split_onsets.event_term | Split onsets of an event_term object |
| standard_error | standard_error |
| standard_error.fmri_latent_lm | Calculate the standard error for an fmri_latent_lm object |
| stats | stats |
| sub_basis | sub_basis |
| term_indices | term_indices |
| term_matrices | term_matrices |
| term_matrices.fmri_model | Construct term matrices for an fMRI model |
| term_names | term_names |
| to_glt | convert a contrast to an AFNI 'GLT' |
| trialwise | trialwise |
| unit_contrast | Unit Contrast |
| wrap_chunked_lm_results | a beastly function that unravels multiple chunk-wise model... |
| write_glt | write a GLT file to disk |
