Package index • rMVPA

All Functions

All functions exported by rMVPA

MVPAModels: Pre-defined MVPA Classification Models

add_interaction_contrasts(): Add Interaction Contrasts to an msreve_design

average_labels(): Average NeuroVec Data by Labels

balance_partitions(): Balance Cross-Validation Partitions

binary_classification_result(): Classification results for binary outcome

category_rdm(): Create Hypothesis RDM from Category Structure

classification_result(): Create a classification_result instance

combine_prediction_tables(): Combine prediction tables

contrast_rsa_model(): Constructor for contrast_rsa_model

contrasts(): Generate Contrast Matrices

create_dist(): Create a Distance Function Object

bootstrap_blocked_cross_validation() blocked_cross_validation() sequential_blocked_cross_validation() custom_cross_validation(): bootstrap_blocked_cross_validation

crossv_block(): Block Cross-Validation Data Preparation

crossv_k(): K-fold Cross-Validation Data Preparation

crossval_samples(): Cross-validation samples

custom_performance(): Apply Custom Performance Metric to Prediction Result

data_sample(): Extract Sample from Dataset

cordist() mahadist() eucdist() robustmahadist() pcadist(): Distance Function Constructors

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

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

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(<manova_model>) merge_results(<mvpa_model>) merge_results(<binary_classification_result>) merge_results(<regression_result>) merge_results(<multiway_classification_result>) merge_results(<regional_mvpa_result>) merge_results(<rsa_model>) merge_results(<vector_rsa_model>) merge_results(<feature_rsa_model>): Merge Results for MANOVA Model

merge_results(): Merge Multiple Results

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

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

predict_model(): Predict Model Output

predicted_class(): Calculate the Predicted Class from Probability Matrix

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(<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

rsa_design(): Construct a design for an RSA (Representational Similarity Analysis) model

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_regional() run_regional_base(): Region of Interest Based MVPA Analysis

run_searchlight(): Run 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

run_searchlight_base(): A "base" function for searchlight analysis

save_results(): Save searchlight results to disk (S3 generic)

second_order_similarity(): Compute Second-Order Similarity Scores

select_features(): Select Features

strip_dataset(): Strip Dataset from Model Specification

sub_result(<multiway_classification_result>) sub_result(<binary_classification_result>): Subset Multiway Classification Result

sub_result(): Extract Row-wise Subset of a Result

summary(<feature_rsa_model>): Summary Method for Feature RSA Model

table_to_rdm(): Convert Similarity Table to RDM

temporal(): Temporal RDM wrapper for formula usage

temporal_nuisance_for_msreve(): Temporal nuisance RDM at condition level (for MS-ReVE)

temporal_rdm(): Temporal/ordinal nuisance RDM (trial-level)

test_design(): Test Design Extraction

train_indices(): Get Training Indices for a Fold

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

y_test(): Test Labels/Response Extraction

y_train(): Training Labels/Response Extraction