create_rand_coef_mat {bigtime} R Documentation

## Creates a random coefficient matrix

### Description

Creates a random coefficient matrix

### Usage

create_rand_coef_mat(
k,
p,
max_abs_eigval = 0.8,
sparsity_pattern = c("none", "lasso", "hvar"),
sparsity_options = NULL,
decay = 0.5,
...
)


### Arguments

 k Number of time series p Number of lags max_abs_eigval if < 1, then the VAR will be stable sparsity_pattern The sparsity pattern that should be simulated. Options are: "none" for a dense VAR, "lasso" for a VAR with random zeroes, and "hvar" for an elementwise hierarchical sparsity pattern sparsity_options Named list of additional options for when sparsity pattern is lasso or hvar. For lasso the option num_zero determines the number of zeros. For hvar, the options zero_min (zero_max) give the minimum (maximum) of zeroes for each variable in each equation, and the option zeroes_in_self (boolean) determines if any of the coefficients of a variable on itself should be zero. decay How fast should coefficients shrink when the lag increases. ... Not currently used

### Value

Returns a coefficient matrix in companion form of dimension kpxkp.

[Package bigtime version 0.2.1 Index]