fda: fRegress.stderr – R documentation

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fRegress.stderr

Compute Standard errors of Coefficient Functions Estimated by Functional Regression Analysis

Description

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.

Usage

## S3 method for class 'stderr'
fRegress(y, y2cMap, SigmaE, returnMatrix=FALSE, ...)

Arguments

`y`	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`.)
`y2cMap`	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.
`SigmaE`	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.
`returnMatrix`	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.

Value

a named list of length 3 containing:

`betastderrlist`	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.
`bvar`	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.
`c2bMap`	a matrix containing the mapping from response variable coefficients to coefficients for regression coefficients.

Examples

#See the weather data analyses in the file daily.ssc for
#examples of the use of function fRegress.stderr.

fda

Functional Data Analysis

v5.1.9

GPL (>= 2)

Authors

J. O. Ramsay <ramsay@psych.mcgill.ca> [aut,cre], Spencer Graves <spencer.graves@effectivedefense.org> [ctb], Giles Hooker <gjh27@cornell.edu> [ctb]

Initial release

2020-12-16