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Fit a smoothing spline to a matrix of responses, single x.
mspline(x, y, w, df = 5, lambda, thresh = 1e-04, ...)
A list is returned, with a number of components, only some of which are of interest. These are
The value of lambda used (in case df was supplied)
The df used (in case lambda was supplied)
A matrix like y of smoothed responses
y
Self influences (diagonal of smoother matrix)
x variable (numeric vector).
response matrix.
optional weight vector, defaults to a vector of ones.
requested degrees of freedom, as in smooth.spline.
smooth.spline
can provide penalty instead of df.
convergence threshold for df inversion (to lambda).
holdall for other arguments.
Trevor Hastie
This function is based on the ingredients of smooth.spline, and allows for simultaneous smoothing of multiple responses
x=rnorm(100) y=matrix(rnorm(100*10),100,10) fit=mspline(x,y,df=5)
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