Description Usage Arguments Details Value Author(s) References See Also Examples

A special `smooth.construct`

method function for creating tensor product smooths from any
combination of single penalty marginal smooths, using the construction of Wood, Scheipl and Faraway (2013).

1 2 | ```
## S3 method for class 't2.smooth.spec'
smooth.construct(object, data, knots)
``` |

`object` |
a smooth specification object of class |

`data` |
a list containing just the data (including any |

`knots` |
a list containing any knots supplied for basis setup — in same order and with same names as |

Tensor product smooths are smooths of several variables which allow the degree of smoothing to be different with respect
to different variables. They are useful as smooth interaction terms, as they are invariant to linear rescaling of the covariates,
which means, for example, that they are insensitive to the measurement units of the different covariates. They are also useful
whenever isotropic smoothing is inappropriate. See `t2`

, `te`

, `smooth.construct`

and
`smooth.terms`

. The construction employed here produces tensor smooths for which the smoothing penalties are non-overlapping portions of the identity matrix. This makes their estimation by mixed modelling software rather easy.

An object of class `"t2.smooth"`

.

Simon N. Wood simon.wood@r-project.org

Wood, S.N., F. Scheipl and J.J. Faraway (2013) Straightforward intermediate rank tensor product smoothing in mixed models. Statistics and Computing 23: 341-360.

1 | ```
## see ?t2
``` |

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