Description Usage Arguments Details Value Author(s) Examples

The estimation functions of the `smoots`

package estimate the
nonparametric trend function or its derivatives on the rescaled
time interval *[0, 1]*. With this function the derivative estimates can
be rescaled in accordance with a given vector with time points.

1 |

`y` |
a numeric vector or matrix with the derivative estimates obtained
for time points on the interval |

`x` |
a numeric vector of length |

`v` |
the order of derivative that is implemented for |

The derivative estimation process is based on the additive time series model

*y_t = m(x_t) + ε_t,*

where *y_t* is the observed time series with equidistant design,
*x_t* is the rescaled time on *[0, 1]*, *m(x_t)* is a smooth and
deterministic trend function and *ε_t* are stationary errors
with E(eps_[t]) = 0 (see also Beran and Feng, 2002). Since the estimates of
the main smoothing functions in `smoots`

are obtained with regard to the
rescaled time points *x_t*, the derivative estimates returned by these
functions are valid for *x_t* only. Thus, by passing the returned
estimates to the argument `y`

, a vector with the actual time points to
the argument `x`

and the order of derivative of `y`

to the argument
`v`

, a rescaled estimate series is calculated and returned. The function
can also be combined with the numeric output of `confBounds`

.

Note that the trend estimates, even though they are also obtained for the
rescaled time points *x_t*, are still valid for the actual time points.

A numeric vector with the rescaled derivative estimates is returned.

Dominik Schulz (Research Assistant) (Department of Economics, Paderborn University),

Package Creator and Maintainer

1 2 3 4 5 6 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.