Man pages for bbuchsbaum/rMVPA
Multivoxel Pattern Analysis in R
| add_interaction_contrasts | Add Interaction Contrasts to an msreve_design |
| as_roi | Convert object to ROI |
| balance_partitions | Balance Cross-Validation Partitions |
| binary_classification_result | Classification results for binary outcome |
| classification_result | Create a 'classification_result' instance |
| coalesce_join2 | Coalesce Join Two Data Frames |
| combine_custom_randomized | Combine Custom Randomized Searchlight Results |
| combine_custom_standard | Combine Custom Standard Searchlight Results |
| combine_msreve_standard | Combine MS-ReVE (Contrast RSA) Searchlight Results |
| combine_prediction_tables | Combine prediction tables |
| combine_randomized | Combine randomized classifier results |
| combine_rsa_standard | Combine RSA standard classifier results |
| combine_standard | Combine standard classifier results |
| combine_vector_rsa_standard | Combine Vector RSA standard classifier results |
| compute_crossvalidated_means_sl | Compute Cross-Validated Condition Means within a Searchlight |
| compute_performance | Compute Performance for an Object |
| contrast_rsa_model | Constructor for contrast_rsa_model |
| contrasts | Generate Contrast Matrices |
| create_dist | Create a Distance Function Object |
| create_mvpa_folds | Create Cross-Validation Folds |
| create_searchlight_performance | Create Searchlight Performance Object |
| cross_validation | bootstrap_blocked_cross_validation |
| crossval_samples | crossval_samples |
| crossv_block | Block Cross-Validation Data Preparation |
| crossv_bootstrap_block | Block Bootstrap Cross-Validation Data Preparation |
| crossv_k | K-fold Cross-Validation Data Preparation |
| custom_performance | Apply Custom Performance Metric to Prediction Result |
| data_sample | Extract Sample from Dataset |
| distance-constructors | Distance Function Constructors |
| do_merge_results | Merge searchlight results |
| do_randomized | Perform randomized searchlight analysis |
| do_standard | Perform standard searchlight analysis |
| evaluate_model.feature_rsa_model | Evaluate model performance for feature RSA |
| evaluate_model.vector_rsa_model | Evaluate model performance for vector RSA |
| feature_rsa_design | Create a Feature-Based RSA Design |
| feature_rsa_model | Create a Feature-Based RSA Model |
| feature_selection | Feature Selection Methods |
| feature_selector | Create a feature selection specification |
| filter_roi | Filter Region of Interest (ROI) |
| fit_model | Fit Model |
| format_result | Format Result Object |
| gen_sample_dataset | Generate Sample Dataset for MVPA Analysis |
| get_nfolds | Get the Number of Folds |
| get_samples | Get Multiple Data Samples |
| get_searchlight | Generate Searchlight Iterator |
| get_unique_regions | Get Unique Region IDs |
| group_means | Compute Group Means of a Matrix |
| has_crossval | Cross-Validation Availability |
| has_test_set | Test Set Availability |
| kfold_cross_validation | kfold_cross_validation |
| load_model | Load a Pre-defined MVPA Model |
| make_feature_contrasts | Generate Contrasts from a Feature Matrix (Optional PCA) |
| manova_design | Create a MANOVA Design |
| manova_model | Create a MANOVA Model |
| merge_classif_results | Merge Multiple Classification/Regression Results |
| merge_predictions | Merge Predictions |
| merge_results | Merge Multiple Results |
| merge_results.manova_model | Merge Results for MANOVA Model |
| merge_results.regional_mvpa_result | Merge multiple regional MVPA results into a single result. |
| merge_results.rsa_model | Merge Results for RSA Model |
| merge_results.vector_rsa_model | Merge results for vector RSA model |
| msreve_design | Constructor for msreve_design |
| multiway_classification_result | Create a Multiway Classification Result Object |
| mvpa_dataset | Create an MVPA Dataset Object |
| mvpa_design | Create an MVPA Design Object |
| mvpa_iterate | Iterate MVPA Analysis Over Multiple ROIs |
| mvpa_model | Create an MVPA Model |
| MVPAModels | Pre-defined MVPA Classification Models |
| mvpa_surface_dataset | Create a Surface-Based MVPA Dataset Object |
| mvpa_sysinfo | Report System and Package Information for rMVPA |
| new-analysis-overview | Extending the MVPA Framework: Creating a New Analysis Type |
| nobs | Get Number of Observations |
| nresponses | Number of Response Categories |
| orthogonalize_contrasts | Orthogonalize a Contrast Matrix |
| performance | Compute Performance Metrics |
| performance.regression_result | Calculate Performance Metrics for Regression Result |
| pool_randomized | Combine randomized searchlight results by pooling |
| predicted_class | Calculate the Predicted Class from Probability Matrix |
| predict_model | Predict Model Output |
| prep_regional | Prepare regional data for MVPA analysis |
| print.feature_rsa_design | Print Method for Feature RSA Design |
| print.feature_rsa_model | Print Method for Feature RSA Model |
| print.mvpa_sysinfo | Print mvpa_sysinfo Object |
| print.vector_rsa_design | Print Method for vector_rsa_design |
| print.vector_rsa_model | Print Method for vector_rsa_model |
| prob_observed | Probability of Observed Class |
| regional_mvpa_result | Create a 'regional_mvpa_result' instance |
| register_mvpa_model | Register a Custom MVPA Model |
| regression_result | Create a Regression Result Object |
| rMVPA | rMVPA: A package for multi-voxel pattern analysis (MVPA) |
| rMVPA-package | rMVPA: Multivoxel Pattern Analysis in R |
| rsa_design | Construct a design for an RSA (Representational Similarity... |
| rsa_model | Construct an RSA (Representational Similarity Analysis) model |
| run_custom_regional | Run a Custom Analysis Function Regionally |
| run_custom_searchlight | Run a Custom Analysis Function in a Searchlight |
| run_future | Run Future |
| run_regional-methods | Region of Interest Based MVPA Analysis |
| run_searchlight | Run Searchlight Analysis |
| run_searchlight_base | A "base" function for searchlight analysis |
| run_searchlight.contrast_rsa_model | Run Searchlight Analysis for Contrast RSA Model |
| run_searchlight.default | Default method for run_searchlight |
| run_searchlight.vector_rsa | run_searchlight method for vector_rsa_model |
| second_order_similarity | Compute Second-Order Similarity Scores |
| select_features-methods | Select Features |
| strip_dataset | Strip Dataset from Model Specification |
| strip_dataset.default | Default method for strip_dataset generic |
| sub_result | Extract Row-wise Subset of a Result |
| sub_result.binary_classification_result | Subset Binary Classification Result |
| sub_result.multiway_classification_result | Subset Multiway Classification Result |
| summary.feature_rsa_model | Summary Method for Feature RSA Model |
| test_design | Test Design Extraction |
| train_indices | Get Training Indices for a Fold |
| train_model | Train a classification, regression, or representational... |
| train_model.contrast_rsa_model | Train method for contrast_rsa_model |
| train_model.manova_model | Train a MANOVA Model |
| train_model.mvpa_model | Train an MVPA Model |
| train_model.rsa_model | Train an RSA Model |
| train_model.vector_rsa_model | Train a vector RSA model |
| transform_contrasts | Apply Transformations to an Existing Contrast Matrix |
| tune_grid | Extract Tuning Grid |
| twofold_blocked_cross_validation | twofold_blocked_cross_validation |
| vector_rsa_design | Construct a design for a vectorized RSA model |
| vector_rsa_model | Create a vectorized RSA model |
| wrap_out | Wrap output results |
| wrap_output | Wrap Output |
| y_test | Test Labels/Response Extraction |
| y_train | Training Labels/Response Extraction |
