sm: sm.regression.autocor – R documentation

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sm.regression.autocor

Nonparametric regression with autocorrelated errors

Description

This function estimates nonparametrically the regression function of y on x when the error terms are serially correlated.

Usage

sm.regression.autocor(x = 1:n, y, h.first, minh, maxh, method = "direct", ...)

Arguments

`y`	vector of the response values
`h.first`	the smoothing parameter used for the initial smoothing stage.
`x`	vector of the covariate values; if unset, it is assumed to be `1:length(y)`.
`minh`	the minimum value of the interval where the optimal smoothing parameter is searched for (default is 0.5).
`maxh`	the maximum value of the interval where the optimal smoothing parameter is searched for (default is 10).
`method`	character value which specifies the optimality criterium adopted; possible values are `"no.cor"`, `"direct"` (default), and `"indirect"`.
`...`	other optional parameters are passed to the `sm.options` function, through a mechanism which limits their effect only to this call of the function. Those relevant for this function are the following: `ngrid`, `display`; see the documentation of `sm.options` for their description.

Details

see Section 7.5 of the reference below.

Value

a list as returned from sm.regression called with the new value of smoothing parameter, with an additional term $aux added which contains the initial value h.first, the estimated curve using h.first, the autocorrelation function of the residuals from the initial fit, and the residuals.

Side Effects

a new suggested value for h is printed; also, if the parameter display is not equal to "none", graphical output is produced on the current graphical device.

References

Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.