Liu, Delong (NIH/CIT) [C] <liud2 <at> mail.nih.gov> writes:
>>>
I want to extract estimated coeffiicents of each local polynomial at
given x from loess(), locfit(), or KernSmooth(). Can some experts
provide me with suggestions? Thanks.
>>
Try
cars.lo <- loess(dist ~ speed, cars)
str(cars.lo)
List of 17
$ n : int 50
$ fitted : num [1:50] 5.89 5.89 12.57 12.57 15.37 ...
$ residuals: Named num [1:50] -3.894 4.106 -8.568 9.432 0.631 ...
... omitted
..$ cell : num 0.2
..$ family : chr "gaussian"
..$ iterations : num 1
$ kd :List of 5
..$ parameter: Named int [1:7] 1 50 2 19 11 1049 849
.. ..- attr(*, "names")= chr [1:7] "d" "n" "vc" "nc" ...
..$ a : int [1:19] 1 1 1 1 1 1 1 0 0 0 ...
..$ xi : num [1:19] 15 12 19 9 13 17 20 0 0 0 ...
..$ vert : num [1:2] 3.90 25.11
..$ vval : num [1:22] 5.71 1.72 96.46 10.88 41.21 ...
$ call : language loess(formula = dist ~ speed, data = cars)
Looks like kd holds information about the polynomials. Then, try
getAnywhere(predict.loess)
which will show you that the real work is done in function predLoess.
Trying again
getAnywhere(predLoess)
you get an idea how the parameters are used for prediction.
fit[inside] <- .C(R_loess_ifit, as.integer(kd$parameter),
as.integer(kd$a), as.double(kd$xi), as.double(kd$vert),
as.double(kd$vval), as.integer(M1), as.double(x.evaluate[inside,
]), fit = double(M1))$fit
Dieter
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