This function compares the fit of several mlVAR models. Since an mlVAR model is a combination of univariate models this function will compare the fits for each univariate model.

1 |

`...` |
Any number of objects obtained from |

Important to note is that the number of observations must be equal to make models comparable. If the lags are different and `compareToLags`

was not used in `mlVAR`

this function will stop with an informative error message.

Sacha Epskamp (mail@sachaepskamp.com)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
## Not run:
### Small example ###
# Simulate data:
Model <- mlVARsim(nPerson = 50, nNode = 3, nTime = 50, lag=1)
# Estimate using different methods:
fit1 <- mlVAR(Model$Data, vars = Model$vars, idvar = Model$idvar, lags = 1,
temporal = "correlated")
fit2 <- mlVAR(Model$Data, vars = Model$vars, idvar = Model$idvar, lags = 1,
temporal = "orthogonal")
fit3 <- mlVAR(Model$Data, vars = Model$vars, idvar = Model$idvar, lags = 1,
temporal = "fixed")
# Compare models:
mlVARcompare(fit1,fit2,fit3)
## End(Not run)
``` |

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