check_input_largevar: Input checker for largevar function

In Largevars: Testing Large VARs for the Presence of Cointegration

Input checker for largevar function

Description

This is an internal function that checks the validity of the inputs of the largevar function.

Usage

check_input_largevar(
  data,
  k,
  r,
  fin_sample_corr,
  plot_output,
  significance_level
)

Arguments

data	a numeric matrix where columns contain the individual time series that will be examined for presence of cointegrating relationships
k	The number of lags we wish to employ in the VECM form (default: k=1)
r	The number of cointegrating relationships we impose on the H1 hypothesis (default: r=1)
fin_sample_corr	A boolean variable indicating whether we wish to employ finite sample correction on our test statistic. Default is false
plot_output	A boolean variable indicating whether we wish to generate the distribution of the eigenvalues (default: TRUE)
significance_level	Specify the significance level at which the decision about the H0 should be made. For r=1 this can be any level of significance. For r=2 and r=3, the significance level input will be rounded up to the nearest of the following: 0.1, 0.05, 0.025, 0.01. If the significance level is larger than 0.1, the decision will be made at the 10% level. For r>3 only the test statistic is returned. For an empirical p-value for r>3 use the sim_function fun. in the package.

Value

Nothing (or warning message) if all inputs are correct, and an error message otherwise.

Largevars documentation built on June 8, 2025, 11:18 a.m.