Package index • rMVPA

All Functions

All functions exported by rMVPA

MVPAModels: Pre-defined MVPA Classification Models

binary_classification_result(): Classification results for binary outcome

classification_result(): Create a classification_result instance

combine_prediction_tables(): Combine prediction tables

compute_performance(): Compute Performance for an Object

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(): crossval_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 Method for Feature RSA Model

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_samples(): Get Multiple Data Samples

get_searchlight(): Generate Searchlight Iterator

group_means(): Compute Group Means of a Matrix

has_crossval(): Requires cross-validation to be performed

has_test_set(): Test Set Availability

kfold_cross_validation(): kfold_cross_validation

load_model(): Load a Pre-defined MVPA Model

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(<feature_rsa_model>): Merge Multiple Results for Feature RSA Model

merge_results(<regional_mvpa_result>): Merge regional MVPA results

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

new-analysis-overview: Extending the MVPA Framework: Creating a New Analysis Type

nobs(): Get Number of Observations

nresponses(): Number of Response Categories

pairwise_dist(<cordist>): Compute Pairwise Correlation Distances

pairwise_dist(<euclidean>): Compute Pairwise Euclidean Distances

pairwise_dist(<mahalanobis>): Compute Pairwise Mahalanobis Distances

pairwise_dist(<pcadist>): Compute Pairwise PCA-Based Distances

pairwise_dist(<robustmahadist>): Compute Pairwise Robust Mahalanobis Distances

performance(): Compute Performance Metrics

performance(<regression_result>): Calculate Performance Metrics for Regression Result

predict_model.feature_rsa_model(): Predict Method for Feature RSA Model

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

rMVPA: rMVPA: A package for multi-voxel pattern analysis (MVPA)

regional_mvpa_result(): Create a regional_mvpa_result instance

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_regional(): Region of Interest Based MVPA Analysis

run_regional(<default>): Default method for run_regional

run_regional(<feature_rsa_model>): Specialized run_regional method for feature_rsa_model

run_regional(<mvpa_model>): Specialized run_regional method for mvpa_model

run_regional(<rsa_model>): Specialized run_regional method for rsa_model

run_regional_base(): A "base" function that does the standard regional analysis pipeline

run_searchlight(): Run Searchlight Analysis

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

second_order_similarity(): Compute Second-Order Similarity Scores

select_features(<FTest>): Perform feature selection using the F-test method

select_features(): Select Features

select_features(<catscore>): Perform feature selection using the CATSCORE method

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_model(): Train 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

tune_grid(): Tune Grid Extraction

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