Construct observation and covariate matrices for a vector autoregressive model

nmfkc.ar generates the observation matrix and covariate matrix corresponding to a specified autoregressive lag order.

If the input Y is a ts object, its time properties are preserved in the "tsp_info" attribute, adjusted for the lag. Additionally, the column names of Y and A are set to the corresponding time points.

Usage

nmfkc.ar(Y, degree = 1, intercept = TRUE)

Arguments

Y

An observation matrix (P x N) or a ts object. If Y is a ts object (typically N x P), it is automatically transposed to match the (P x N) format.

degree

The lag order of the autoregressive model. The default is 1.

intercept

Logical. If TRUE (default), an intercept term is added to the covariate matrix.

Value

A list containing:

Y

Observation matrix (P x N_A) used for NMF. Includes adjusted "tsp_info" attribute and time-based column names.

A

Covariate matrix (R x N_A) constructed according to the specified lag order. Includes adjusted "tsp_info" attribute and time-based column names.

A.columns

Index matrix used to generate A.

degree.max

Maximum lag order.

See also

nmfkc, nmfkc.ar.degree.cv, nmfkc.ar.stationarity, nmfkc.ar.DOT