lambda2df

a vector containing the argument values used in the
    smooth of the data.

argvals

the basis object used in the smoothing of the data.

basisobj

the weight vector, if any, that was used in the smoothing
    of the data.

wtvec

the linear differential operator object used to defining
    the roughness penalty employed in smoothing the data.

Lfdobj

lambda

logical:  If TRUE,  a two-dimensional is returned using a
    special class from the Matrix package.

returnMatrix

The degree of roughness of an estimated function is controlled by a
smoothing parameter $lambda$ that directly multiplies the penalty.
However, it can be difficult to interpret or choose this value, and it
is often easier to determine the roughness by choosing a value that is
equivalent of the degrees of freedom used by the smoothing procedure.
This function converts a multipler $lambda$ into a degrees of freedom value.

smooth

These functions were developed to support functional data
        analysis as described in Ramsay, J. O. and Silverman, B. W.
        (2005) Functional Data Analysis. New York: Springer.  They were
        ported from earlier versions in Matlab and S-PLUS.  An
        introduction appears in Ramsay, J. O., Hooker, Giles, and
        Graves, Spencer (2009) Functional Data Analysis with R and
        Matlab (Springer). The package includes data sets and script
        files working many examples including all but one of the 76
        figures in this latter book.  Matlab versions of the code and
        sample analyses are no longer distributed through CRAN, as they
        were when the book was published.  For those, ftp from
        http://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/
        There you find a set of .zip files containing the functions and
        sample analyses, as well as two .txt files giving instructions for
        installation and some additional information.

lambda2df: Convert Smoothing Parameter to Degrees of Freedom

Description

Usage

Arguments

Value

See Also