Module fdata 

Functional data operations: mean, center, derivatives, norms, and geometric median.

Structs

Deriv2DResult

Result of 2D partial derivatives.

Enums

DerivDomain

Domain specification for deriv, carrying the dimension-specific grid and parameters.

DerivResult

Result of deriv, unifying the 1D and 2D output shapes.

NormalizationMethod

Normalization method for functional data.

Functions

center

Center functional data by subtracting the mean function via a unified Dim dispatch.

depth_based_median

Return the index of the deepest curve under the Fraiman-Muniz depth measure.

deriv

Compute numerical derivatives of functional data (parallelized over rows).

functional_covariance

Compute the M×M sample covariance matrix of functional data (Bessel-corrected, ddof = n-1).

functional_std

Compute pointwise sample standard deviation of functional data (ddof = n-1).

functional_variance

Compute pointwise sample variance of functional data (Bessel-corrected, ddof = n-1).

geometric_median

Compute the geometric median (L1 median) of functional data using Weiszfeld’s algorithm.

mean

Compute the mean function for 1D or 2D functional data via a unified Dim dispatch.

norm_lp

Compute Lp norm for each sample via a unified Dim dispatch.

normalize

Normalize functional data using the specified method.

normalize_with_argvals

Normalize functional data with an evaluation grid.

trim_mean

Compute the depth-trimmed mean of functional data.