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Specification Testing

Identify the parametric form of a model


archtestEngle test for residual heteroscedasticity
autocorrSample autocorrelation
parcorrSample partial autocorrelation
crosscorrSample cross-correlation
corrplotPlot variable correlations
lbqtestLjung-Box Q-test for residual autocorrelation
collintestBelsley collinearity diagnostics
adftestAugmented Dickey-Fuller test
kpsstestKPSS test for stationarity
lmctestLeybourne-McCabe stationarity test
pptestPhillips-Perron test for one unit root
vratiotestVariance ratio test for random walk
i10testPaired integration and stationarity tests
egcitestEngle-Granger cointegration test
jcitestJohansen cointegration test
jcontest Johansen constraint test
chowtestChow test for structural change
cusumtestCusum test for structural change
recregRecursive linear regression

Examples and How To

Box-Jenkins Model Selection

Use the Box-Jenkins methodology to select an ARIMA model.

Detect Autocorrelation

Estimate the ACF and PACF, or conduct the Ljung-Box Q-test.

Detect ARCH Effects

Test for autocorrelation in the squared residuals, or conduct Engle’s ARCH test.

Unit Root Tests

Conduct unit root tests on time series data.

Assess Stationarity of a Time Series

Check whether a linear time series is a unit root process.

Identifying Single Cointegrating Relations

The Engle-Granger test for cointegration and its limitations.

Identifying Multiple Cointegrating Relations

Learn about the Johansen test for cointegration.

Check Model Assumptions for Chow Test

Check the model assumptions for a Chow test.

Power of the Chow Test

Estimate the power of a Chow test using a Monte Carlo simulation.


Econometric Modeling

Understand model-selection techniques and Econometrics Toolbox™ features.

Box-Jenkins Methodology

The Box-Jenkins methodology is a five-step process for identifying, selecting, and assessing conditional mean models (for discrete, univariate time series data).

Autocorrelation and Partial Autocorrelation

Autocorrelation and partial autocorrelation measure is the linear dependence of a variable with itself at two points in time.

Ljung-Box Q-Test

The Ljung-Box Q-test is a quantitative way to test for autocorrelation at multiple lags jointly.

Engle’s ARCH Test

Engle’s ARCH test is a Lagrange multiplier test to assess the significance of ARCH effects.

Unit Root Nonstationarity

Learn how to model a unit root process or test for one.

Vector Autoregression (VAR) Models

Learn the characteristics of vector autoregression models and how to create them.

Cointegration and Error Correction Analysis

Learn about cointegrated time series and error correction models.

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