FCVARlagSelect | R Documentation |

`FCVARlagSelect`

takes a matrix of variables and performs lag
selection on it by using the likelihood ratio test. Output and test
results are printed to the screen.

FCVARlagSelect(x, kmax, r, order, opt)

`x` |
A matrix of variables to be included in the system. |

`kmax` |
The maximum number of lags in the system. |

`r` |
The cointegrating rank.This is often set equal to |

`order` |
The order of serial correlation for white noise tests. |

`opt` |
An S3 object of class |

An S3 object of type `FCVAR_lags`

containing the results
from repeated estimation of the FCVAR model with different orders
of the autoregressive lag length.
Note that row `j`

of each of the vectors in the `FCVAR_lags`

object
contains the associated results for lag length `j+1`

.
The `FCVAR_lags`

object includes the following parameters:

`D`

A (

`kmax`

+ 1) x 2 vector of estimates of d and b.`loglik`

A (

`kmax`

+ 1) x 1 vector of log-likelihood values.`LRtest`

A (

`kmax`

+ 1) x 1 vector of likelihood ratio test statistics for tests of significance of*Γ_{j+1}*.`pvLRtest`

A (

`kmax`

+ 1) x 1 vector of P-values for the likelihood ratio tests of significance of*Γ_{j+1}*.`i_aic`

The lag corresponding to the minimum value of the Akaike information criteria.

`aic`

A (

`kmax`

+ 1) x 1 vector of values of the Akaike information criterion.`i_bic`

The lag corresponding to the minimum value of the Bayesian information criteria.

`bic`

A (

`kmax`

+ 1) x 1 vector of values of the Bayesian information criterion.`pvMVq`

A scalar P-value for the Q-test for multivariate residual white noise.

`pvWNQ`

A (

`kmax`

+ 1) x 1 vector of P-values for the Q-tests for univariate residual white noise.`pvWNLM`

A (

`kmax`

+ 1) x 1 vector of P-values for the LM-tests for univariate residual white noise.`kmax`

The maximum number of lags in the system.

`r`

The cointegrating rank. This is often set equal to

`p`

, the number of variables in the system, since it is better to overspecify than underspecify the model.`p`

The number of variables in the system.

`cap_T`

The sample size.

`order`

The order of serial correlation for white noise tests.

`opt`

An S3 object of class

`FCVAR_opt`

that stores the chosen estimation options, generated from`FCVARoptions()`

.

`FCVARoptions`

to set default estimation options.
`FCVARestn`

is called repeatedly within this function
for each candidate lag order.
`summary.FCVAR_lags`

prints a summary of the output of `FCVARlagSelect`

to screen.

Other FCVAR specification functions:
`FCVARbootRank()`

,
`FCVARrankTests()`

,
`summary.FCVAR_lags()`

,
`summary.FCVAR_ranks()`

opt <- FCVARoptions() opt$gridSearch <- 0 # Disable grid search in optimization. opt$dbMin <- c(0.01, 0.01) # Set lower bound for d,b. opt$dbMax <- c(2.00, 2.00) # Set upper bound for d,b. opt$constrained <- 0 # Impose restriction dbMax >= d >= b >= dbMin ? 1 <- yes, 0 <- no. x <- votingJNP2014[, c("lib", "ir_can", "un_can")] FCVARlagSelectStats <- FCVARlagSelect(x, kmax = 3, r = 3, order = 12, opt)

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