| checkKband | R Documentation |
Analyze whether signals are k-band limited by comparing low-frequency and high-frequency Fourier coefficients using eigendecomposition and statistical testing. Builds graph and computes Laplacian directly from SGWT data.
checkKband(
SG,
signals = NULL,
alpha = 0.05,
verbose = TRUE,
k = 25,
laplacian_type = "normalized"
)
SG |
SGWT object with Data slot (from initSGWT) |
signals |
Character vector of signal names to analyze. If NULL, uses all signals from SG$Data$signals |
alpha |
Significance level for Wilcoxon test (default: 0.05) |
verbose |
Logical; if TRUE, print progress messages (default: TRUE) |
k |
Number of nearest neighbors for graph construction (default: 25) |
laplacian_type |
Type of Laplacian ("unnormalized", "normalized", or "randomwalk") (default: "normalized") |
List containing:
Logical; TRUE if all signals are k-band limited
Integer; knee point index for low-frequency eigenvalues
Integer; knee point index for high-frequency eigenvalues
List with per-signal test results including p-values and Fourier coefficients
# Create example data
data <- data.frame(x = runif(100), y = runif(100),
signal1 = rnorm(100), signal2 = rnorm(100))
# Initialize SGWT object (no need to run runSpecGraph)
SG <- initSGWT(data, signals = c("signal1", "signal2"))
# Check k-band limited property
result <- checkKband(SG, signals = c("signal1", "signal2"), k = 30)
if (result$is_kband_limited) {
cat("All signals are k-band limited")
}
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