# Construct predictor blocks for time series models

### Description

Construct blocks of original and lagged values for autoregressive time
series models with exogenous inputs. The typical use case is to supply the
output as `newdata`

argument to the
`predict`

method of robust groupwise least
angle regression models.

### Usage

1 |

### Arguments

`x` |
a numeric matrix or data frame containing the exogenous predictor series. |

`y` |
a numeric vector containing the response series. |

`p` |
an integer giving the number of lags to include (defaults to 2). |

`subset` |
a logical or integer vector defining a subset of observations from which to construct the matrix of predictor blocks. |

`intercept` |
a logical indicating whether a column of ones should be added to the matrix of predictor blocks to account for the intercept. |

### Value

A matrix containing blocks of original and lagged values of the
time series `y`

and `x`

.

### Author(s)

Andreas Alfons

### See Also

`predict.tslars`

, `tslars`

,
`predict.tslarsP`

, `tslarsP`

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.