API

The WebAssembly bindings provide a high-performance interface to the core Rust library, mirroring the Rust API structure.

StreamingLowess and OnlineLowess are documented separately: wasm-streaming.md, wasm-online.md

When to Use

• Dataset fits in memory
• Need intervals, cross-validation, or diagnostics
• Processing complete files

Classes

Lowess

The Lowess class is the main entry point for batch smoothing.

Constructor:

const { Lowess } = require('fastlowess-wasm');

const model = new Lowess({ fraction: 0.5, iterations: 3 });
console.log("typeof fit:", typeof model.fit);

typeof fit: function

• options: An object containing LowessOptions fields.

Methods:

const { Lowess } = require('fastlowess-wasm');

const n = 100;
const x = Float64Array.from({ length: n }, (_, i) => i * 2 * Math.PI / (n - 1));
const y = Float64Array.from(x, xi => Math.sin(xi) + 0.1);

const model = new Lowess({ fraction: 0.5 });
const result = model.fit(x, y);
console.log("Fraction used:", result.fraction_used);

Fraction used: 0.5

• x: Float64Array of input x values.
• y: Float64Array of input y values.
• Returns: A LowessResult object.

See wasm-streaming.md for the StreamingLowess class.

See wasm-online.md for the OnlineLowess class.

Options Structures

LowessOptions

Field	Type	Default	Description
fraction	number	0.67	Smoothing fraction (bandwidth)
iterations	number	3	Number of robustifying iterations
delta	number	NaN	Interpolation distance (NaN for auto)
weight_function	string	"tricube"	Weight function name
robustness_method	string	"bisquare"	Robustness method name
scaling_method	string	"mad"	Residual scaling method
boundary_policy	string	"extend"	Boundary handling policy
zero_weight_fallback	string	"use_local_mean"	Zero-weight handling
auto_converge	number	null	Auto-convergence tolerance
confidence_intervals	number	null	Confidence level (e.g., 0.95)
prediction_intervals	number	null	Prediction level (e.g., 0.95)
return_diagnostics	boolean	false	Include diagnostics in result
return_residuals	boolean	false	Include residuals in result
return_robustness_weights	boolean	false	Include weights in result
return_se	boolean	false	Return standard errors
parallel	boolean	true	Enable parallel execution
cv_method	string	"kfold"	CV method ("kfold" or "loocv") (Batch only)
cv_k	number	5	Number of folds for k-fold CV (Batch only)
cv_fractions	number[]	null	Fractions to test for cross-validation (Batch only)
cv_seed	number	null	Random seed for cross-validation shuffling (Batch only)
custom_weights	Float64Array	null	Per-observation case weights — passed to fit(), not the options object (Batch only)

See wasm-streaming.md for StreamingOptions.

See wasm-online.md for OnlineOptions.

Result Structure

See wasm-online.md for OnlineOutput.

LowessResult

Field	Type	Description
x	Float64Array	Sorted x values
y	Float64Array	Smoothed y values
fraction_used	number	Fraction used (set or selected by CV)
iterations_used	number | undefined	Robustness iterations actually performed
standard_errors	Float64Array | undefined	Per-point standard errors
confidence_lower	Float64Array | undefined	Lower confidence bounds
confidence_upper	Float64Array | undefined	Upper confidence bounds
prediction_lower	Float64Array | undefined	Lower prediction bounds
prediction_upper	Float64Array | undefined	Upper prediction bounds
residuals	Float64Array | undefined	Residuals (if return_residuals)
robustness_weights	Float64Array | undefined	Robustness weights (if return_robustness_weights)
cv_scores	Float64Array | undefined	CV score per tested fraction
diagnostics	Diagnostics | undefined	Fit metrics (if return_diagnostics)

Diagnostics

Field	Type	Description
rmse	number	Root Mean Squared Error
mae	number	Mean Absolute Error
r_squared	number	R-squared
residual_sd	number	Residual standard deviation
effective_df	number | undefined	Effective degrees of freedom
aic	number | undefined	AIC
aicc	number | undefined	AICc

Options

weight_function

See: Weight Functions

• "tricube" (default)
• "epanechnikov"
• "gaussian"
• "uniform" (alias: "boxcar")
• "biweight" (alias: "bisquare")
• "triangle" (alias: "triangular")
• "cosine"

robustness_method

See: Robustness

• "bisquare" (default; alias: "biweight")
• "huber"
• "talwar"

boundary_policy

See: Boundary Handling

• "extend" (default; alias: "pad")
• "reflect" (alias: "mirror")
• "zero"
• "noboundary" (alias: "none")

scaling_method

See: Scaling Methods

• "mad" (default; alias: "median_absolute_deviation")
• "mar" (alias: "median_absolute_residual")
• "mean" (alias: "mean_absolute_residual")

zero_weight_fallback

See: Parameters

• "use_local_mean" (default; aliases: "local_mean", "mean")
• "return_original" (alias: "original")
• "return_none" (alias: "none")

merge_strategy

See wasm-streaming.md.

update_mode

See wasm-online.md.

Example

const { Lowess } = require('fastlowess-wasm');

const x = new Float64Array([1, 2, 3, 4, 5]);
const y = new Float64Array([2.1, 4.0, 6.2, 8.0, 10.1]);

// Fit data
const model = new Lowess({ fraction: 0.5 });
const result = model.fit(x, y);

console.log("Smoothed Y:", result.y);

Smoothed Y: Float64Array(5) [ 2.1, 4, 6.2, 8, 10.1 ]