PluginForecasting API Reference

The PluginForecasting adds advanced time-series prediction capabilities to the Velo Plot. It implements several statistical forecasting models natively in TypeScript.

Initialization

import { createChart } from 'velo-plot/scientific';
import { PluginForecasting } from 'velo-plot/plugins/forecasting';

const chart = createChart({ ... });
await chart.use(PluginForecasting({
  defaultOptions: {
    method: 'holtWinters',
    horizon: 50
  }
}));

API Reference

Once registered, the plugin exposes its API through chart.forecasting.

forecast(data, options)

Generates a forecast for the provided raw data, or for an existing series when a series id string is passed.

Parameters:

• data: SeriesData | number[] | Float32Array | string - The historical data, or a series id.
• options: ForecastingOptions - Configuration for the forecast.

Returns: ForecastingResult

// Forecast an existing series by id
const result = chart.forecasting.forecast('s1', { method: 'arima', horizon: 50 });
chart.forecasting.visualize(result); // shaded confidence band + dashed line

forecastSeries(seriesId, options)

Generates a forecast for a specific series already present in the chart.

Parameters:

• seriesId: string - ID of the series to analyze.
• options: ForecastingOptions - Configuration for the forecast.

Returns: Promise<ForecastingResult>

visualize(result, config?)

Renders the forecast on the chart overlay.

Parameters:

• result: ForecastingResult - The result from a forecast call.
• config: ForecastingVisualizationConfig - (Optional) Styling configuration.

Returns: string (The visualization ID).

clear(id?)

Removes active forecast visualizations.

Parameters:

• id: string - (Optional) ID of a specific visualization to remove. If omitted, all forecasts are cleared.

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Interfaces

ForecastingOptions

Property	Type	Description
method	string	Method to use (see below)
horizon	number	Number of points to project
confidence	number	(Optional) Confidence level (0-1)
params	ForecastingParams	Method-specific parameters

ForecastingMethod

All methods are implemented and return finite forecasts with confidence bands. No public method throws for a supported method (as of v2.2.0).

Method	Description	Uncertainty grows with horizon
'sma'	Simple Moving Average (flat projection at trailing average)	no
'wma'	Weighted Moving Average (linear weights on trailing window)	no
'ema'	Exponential Moving Average (flat at last EMA)	no
'expSmoothing'	Simple Exponential Smoothing (SES)	no
'holt'	Double Exponential Smoothing (trend-aware)	yes
'holtWinters'	Triple Exponential Smoothing (trend + seasonality)	yes
'linear'	Linear Trend Projection (least-squares fit)	yes
'arima'	ARIMA(p,d,q) via the two-stage Hannan-Rissanen procedure	yes

ARIMA falls back to Holt's linear trend when the history is too short to fit the requested orders, so it is always safe to call.

ForecastingParams

Property	Type	Description
alpha	number	Smoothing factor for level
beta	number	Smoothing factor for trend
gamma	number	Smoothing factor for seasonality
period	number	Seasonal cycle length
windowSize	number	Window size for SMA/WMA
p	number	ARIMA autoregressive order (default 1)
d	number	ARIMA differencing order (default 1)
q	number	ARIMA moving-average order (default 0)

Confidence bands

Every forecast returns lowerBound / upperBound computed from in-sample one-step residuals. The band half-width is z(confidence) · σ · √h for trend/AR models (widening with the horizon h) and z(confidence) · σ for the flat moving-average methods. Set the level via options.confidence (default 0.95). Render the shaded band with visualize(result) or the band series type.

ForecastingResult

Property	Type	Description
xValues	number[]	Projected X coordinates
yValues	number[]	Projected Y values
lowerBound	number[]	Lower confidence limit
upperBound	number[]	Upper confidence limit
metadata	object	Fit statistics: mse, rmse, mae, r2, confidence

Known limitations

• Unknown method strings throw — only documented methods (sma, ema, wma, linear, expSmoothing, holt, holtWinters, arima) are supported.