STSLIB::StatsCluster Class Reference

Cluster permutation testing. More...

#include <sts_cluster.h>

Static Public Member Functions
static StatsClusterResult	permutationTest (const QVector< Eigen::MatrixXd > &dataA, const QVector< Eigen::MatrixXd > &dataB, const Eigen::SparseMatrix< int > &adjacency, int nPermutations=1024, double clusterAlpha=0.05, double pThreshold=0.05, StatsTailType tail=StatsTailType::Both)
static StatsClusterResult	oneSamplePermutationTest (const QVector< Eigen::MatrixXd > &data, const Eigen::SparseMatrix< int > &adjacency, double threshold, int nPermutations, StatsTailType tail)
static StatsClusterResult	fTestPermutationTest (const QVector< QVector< Eigen::MatrixXd > > &conditions, const Eigen::SparseMatrix< int > &adjacency, double threshold, int nPermutations)
static Eigen::MatrixXd	tfce (const Eigen::MatrixXd &statMap, const Eigen::SparseMatrix< int > &adjacency, double E=0.5, double H=2.0, int nSteps=100)

Detailed Description

Cluster permutation testing.

Cluster-based permutation test for comparing two conditions.

Definition at line 84 of file sts_cluster.h.

Member Function Documentation

fTestPermutationTest()

StatsClusterResult StatsCluster::fTestPermutationTest ( const QVector< QVector< Eigen::MatrixXd > > & conditions, const Eigen::SparseMatrix< int > & adjacency, double threshold, int nPermutations )

static

F-test cluster-based permutation test for one-way ANOVA.

Tests for differences across conditions by randomly reassigning condition labels and computing max cluster F-statistics.

Parameters

[in]	conditions	Vector of conditions, each containing per-subject matrices (nVertices x nTimes).
[in]	adjacency	Spatio-temporal adjacency matrix (nVertices*nTimes x nVertices*nTimes).
[in]	threshold	Cluster-forming F-threshold.
[in]	nPermutations	Number of permutations.

Returns

StatsClusterResult with observed F-map (in matTObs), cluster statistics, and p-values.

Since

2.2.0

Definition at line 625 of file sts_cluster.cpp.

oneSamplePermutationTest()

StatsClusterResult StatsCluster::oneSamplePermutationTest ( const QVector< Eigen::MatrixXd > & data, const Eigen::SparseMatrix< int > & adjacency, double threshold, int nPermutations, StatsTailType tail )

static

One-sample cluster-based permutation test.

Tests whether the mean across subjects differs from zero at each vertex x time point using sign-flip permutations.

Parameters

[in]	data	Per-subject data. Each matrix is nVertices x nTimes.
[in]	adjacency	Spatio-temporal adjacency matrix (nVertices*nTimes x nVertices*nTimes).
[in]	threshold	Cluster-forming t-threshold.
[in]	nPermutations	Number of sign-flip permutations.
[in]	tail	Tail type for the test.

Returns

StatsClusterResult with observed t-map, cluster statistics, and p-values.

Since

2.2.0

Definition at line 554 of file sts_cluster.cpp.

permutationTest()

StatsClusterResult StatsCluster::permutationTest ( const QVector< Eigen::MatrixXd > & dataA, const QVector< Eigen::MatrixXd > & dataB, const Eigen::SparseMatrix< int > & adjacency, int nPermutations = 1024, double clusterAlpha = 0.05, double pThreshold = 0.05, StatsTailType tail = StatsTailType::Both )

static

Cluster-based permutation test.

Parameters

[in]	dataA	Per-subject data for condition A. Each matrix is nChannels x nTimes.
[in]	dataB	Per-subject data for condition B. Each matrix is nChannels x nTimes.
[in]	adjacency	Spatial adjacency matrix (nChannels x nChannels).
[in]	nPermutations	Number of permutations (default 1024).
[in]	clusterAlpha	Alpha level for initial thresholding (default 0.05).
[in]	pThreshold	p-value threshold for reporting significant clusters (default 0.05).
[in]	tail	Tail type for the test.

Returns

StatsClusterResult with observed t-map, cluster statistics, and p-values.

Definition at line 62 of file sts_cluster.cpp.

tfce()

MatrixXd StatsCluster::tfce ( const Eigen::MatrixXd & statMap, const Eigen::SparseMatrix< int > & adjacency, double E = 0.5, double H = 2.0, int nSteps = 100 )

static

Threshold-Free Cluster Enhancement (TFCE).

Enhances a statistic map by integrating cluster extent and height over a range of thresholds (Smith & Nichols 2009). Handles both positive and negative values.

Parameters

[in]	statMap	Statistic map (nVertices x nTimes).
[in]	adjacency	Spatio-temporal adjacency matrix (nVertices*nTimes x nVertices*nTimes).
[in]	E	Extent exponent (default 0.5).
[in]	H	Height exponent (default 2.0).
[in]	nSteps	Number of threshold steps (default 100).

Returns

TFCE-enhanced score map (nVertices x nTimes).

Since

2.2.0

Definition at line 688 of file sts_cluster.cpp.

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The documentation for this class was generated from the following files:

• src/libraries/sts/sts_cluster.h
• src/libraries/sts/sts_cluster.cpp