Lagrange multiplier test of model specification

returns
a logical value (`h`

= lmtest(`score`

,`ParamCov`

,`dof`

)`h`

) with the rejection decision
from conducting a Lagrange multiplier test of
model specification at the 5% significance level. `lmtest`

constructs
the test statistic using the score function (`score`

),
the estimated parameter covariance (`ParamCov`

),
and the degrees of freedom (`dof`

).

returns
the rejection decision of the Lagrange multipler test conducted at
significance level `h`

= lmtest(`score`

,`ParamCov`

,`dof`

,`alpha`

)`alpha`

.

If

`score`

and`ParamCov`

are length*k*cell arrays, then all other arguments must be length*k*vectors or scalars.`lmtest`

treats each cell as a separate test, and returns a vector of rejection decisions.If

`score`

is a row cell array, then`lmtest`

returns a row vector.

[1] Davidson, R. and J. G. MacKinnon. *Econometric
Theory and Methods*. Oxford, UK: Oxford University Press,
2004.

[2] Godfrey, L. G. *Misspecification Tests in Econometrics*.
Cambridge, UK: Cambridge University Press, 1997.

[3] Greene, W. H. *Econometric Analysis*.
6th ed. Upper Saddle River, NJ: Pearson Prentice Hall, 2008.

[4] Hamilton, J. D. *Time Series Analysis*.
Princeton, NJ: Princeton University Press, 1994.

`arima`

| `estimate`

| `lratiotest`

| `vgxvarx`

| `waldtest`

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