smart_df: Create random degrees of freedom parameter values close to...

In saviviro/gmvarkit: Estimate Gaussian and Student's t Mixture Vector Autoregressive Models

Create random degrees of freedom parameter values close to given values

Description

random_df generates random M2 degrees of freedom parameter values close to given values, where M2 is number of StMVAR type regimes in the model.

Usage

smart_df(
  M,
  df,
  accuracy,
  which_random = numeric(0),
  model = c("GMVAR", "StMVAR", "G-StMVAR")
)

Arguments

M	For GMVAR and StMVAR models: a positive integer specifying the number of mixture components. For G-StMVAR models: a size (2x1) integer vector specifying the number of GMVAR type components M1 in the first element and StMVAR type components M2 in the second element. The total number of mixture components is M=M1+M2.
df	the old degrees of freedom parameters (of all regimes)
accuracy	a positive real number adjusting how close to the given degrees of freedom parameters the returned df should be.
which_random	a vector with length between 1 and M specifying the mixture components that should be random instead of close to the given degrees of freedom.
model	is "GMVAR", "StMVAR", or "G-StMVAR" model considered? In the G-StMVAR model, the first M1 components are GMVAR type and the rest M2 components are StMVAR type.

Value

GMVAR models:

a numeric vector of length zero.

StMVAR models:

a numeric vector of length M with random entries strictly larger than two.

G-StMVAR models:

a numeric vector of length M2 with random entries strictly larger than two.

saviviro/gmvarkit documentation built on March 8, 2024, 4:15 a.m.