Class Econometrics

java.lang.Object

org.episteme.social.economics.analysis.Econometrics

public class Econometrics
extends Object

Provides econometric tools for analyzing economic data, including time series analysis models like ARIMA (AutoRegressive Integrated Moving Average) and GARCH (Generalized AutoRegressive Conditional Heteroskedasticity).

Since:

1.0

Author:

Silvere Martin-Michiellot, Gemini AI (Google DeepMind)

Method Summary

Modifier and Type	Method	Description
static Real	arima(List<Real> data, int p, int d, int q)	Calculates the Autoregressive Integrated Moving Average (ARIMA) for a given time series.
static Real	garch(List<Real> returns, int p, int q)	Calculates GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) to model volatility.

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

arima

public static Real arima(List<Real> data,
 int p,
 int d,
 int q)

Calculates the Autoregressive Integrated Moving Average (ARIMA) for a given time series.

Note: This is a simplified implementation or placeholder. A full ARIMA implementation requires complex maximum likelihood estimation.

Parameters:

data - The time series data.

p - The order of the autoregressive (AR) term.

d - The degree of differencing (I).

q - The order of the moving average (MA) term.

Returns:

A forecasted value or model parameters (simplified as a single prediction for now).

garch

public static Real garch(List<Real> returns,
 int p,
 int q)

Calculates GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) to model volatility.

Parameters:

returns - The financial returns or time series differenced data.

p - The order of the GARCH terms (lagged variance).

q - The order of the ARCH terms (lagged squared errors).

Returns:

The estimated volatility for the next step.