Function fRegress
carries out a functional regression analysis
of the concurrent kind, and estimates a regression coefficient
function corresponding to each independent variable, whether it is
scalar or functional. This function uses the list that is output by
fRegress
to provide standard error functions for each
regression function. These standard error functions are pointwise,
meaning that sampling standard deviation functions only are computed,
and not sampling covariances.
# S3 method for stderr
fRegress(y, y2cMap, SigmaE, returnMatrix=FALSE, ...)
a named list of length 3 containing:
a list object of length the number of independent variables. Each member contains a functional parameter object for the standard error of a regression function.
a symmetric matrix containing sampling variances and covariances for the matrix of regression coefficients for the regression functions. These are stored column-wise in defining BVARIANCE.
a matrix containing the mapping from response variable coefficients to coefficients for regression coefficients.
the named list that is returned from a call to function
fRegress
, where it is referred to as fRegressList. (R syntax
requires that the first argument of any function beginning with
fRegress.
must begin with y
.)
a matrix that contains the linear transformation that takes the raw
data values into the coefficients defining a smooth functional data
object. Typically, this matrix is returned from a call to function
smooth.basis
that generates the dependent variable objects.
If the dependent variable is scalar, this matrix is an identity
matrix of order equal to the length of the vector.
either a matrix or a bivariate functional data object according to whether the dependent variable is scalar or functional, respectively. This object has a number of replications equal to the length of the dependent variable object. It contains an estimate of the variance-covariance matrix or function for the residuals.
logical: If TRUE, a two-dimensional is returned using a special class from the Matrix package.
optional arguments not used by fRegress.stderr
but needed for
superficial compatibility with fRegress
methods.
Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.
fRegress
,
fRegress.CV
#See the weather data analyses in the file daily.ssc for
#examples of the use of function fRegress.stderr.
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