specify_data_matrices: R6 Class Representing DataMatricesBSVAR

In bsvars: Bayesian Estimation of Structural Vector Autoregressive Models

R6 Class Representing DataMatricesBSVAR

Description

The class DataMatricesBSVAR presents the data matrices of dependent variables, Y, and regressors, X, for the homoskedastic bsvar model.

Public fields

Y

an NxT matrix of dependent variables, Y.

X

an KxT matrix of regressors, X.

Methods

Public methods

• specify_data_matrices$new()

• specify_data_matrices$get_data_matrices()

• specify_data_matrices$clone()

---

Method new()

Create new data matrices DataMatricesBSVAR.

Usage

specify_data_matrices$new(data, p = 1L, exogenous = NULL)

Arguments

data

a (T+p)xN matrix with time series data.

p

a positive integer providing model's autoregressive lag order.

exogenous

a (T+p)xd matrix of exogenous variables. This matrix should not include a constant term.

Returns

New data matrices DataMatricesBSVAR.

---

Method get_data_matrices()

Returns the data matrices DataMatricesBSVAR as a list.

Usage

specify_data_matrices$get_data_matrices()

Examples

data(us_fiscal_lsuw)
YX = specify_data_matrices$new(data = us_fiscal_lsuw, p = 4)
YX$get_data_matrices()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

specify_data_matrices$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

data(us_fiscal_lsuw)
YX = specify_data_matrices$new(data = us_fiscal_lsuw, p = 4)
dim(YX$Y); dim(YX$X)


## ------------------------------------------------
## Method `specify_data_matrices$get_data_matrices`
## ------------------------------------------------

data(us_fiscal_lsuw)
YX = specify_data_matrices$new(data = us_fiscal_lsuw, p = 4)
YX$get_data_matrices()

bsvars documentation built on Oct. 24, 2024, 5:11 p.m.