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update fRegress.Rd
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man/fRegress.Rd

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@@ -223,55 +223,54 @@ fRegress(y, ...)
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or a model specification:
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\describe{
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\item{The \code{fRegress} fit object case:}{A list of class
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\code{fRegress} with the following components:
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\itemize{
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\item{y:} {The first argument in the call to \code{fRegress}.
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This argument is coerced to \code{class} \code{fd} in fda version 5.1.9.
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Prior versions of the package converted it to an \code{fdPar}, but the
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extra structures in that class were not used in any of the
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\code{fRegress} codes.}
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\item{xfdlist:} {The second argument in the call to \code{fRegress}.}
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\item{betalist:} {The third argument in the call to \code{fRegress}.}
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\item{betaestlist:} {A list of length equal to the number of independent
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variables and with members having the same functional parameter
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structure as the corresponding members of \code{betalist}. These are the
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estimated regression coefficient functions.}
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\item{yhatfdobj:} {A functional parameter object (class \code{fdPar})
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if the dependent variable is functional or a vector if the dependent
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variable is scalar. This is the set of predicted by the
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functional regression model for the dependent variable.}
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\item{Cmatinv:} {A matrix containing the inverse of the coefficient
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matrix for the linear equations that define the solution to the
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regression problem. This matrix is required for function
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\code{fRegress.stderr} that estimates confidence regions
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for the regression coefficient function estimates.}
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\item{wt:} {The vector of weights input or inferred.}
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}
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If \code{class(y)} is numeric, the \code{fRegress} object also includes:
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\itemize{
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\item{df:} {The equivalent degrees of freedom for the fit.}
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\item{OCV} {the leave-one-out cross validation score for the model.}
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\item{gcv:} {The generalized cross validation score.}
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}
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If \code{class(y)} is \code{fd} or \code{fdPar}, the
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code{fRegress} object returned also includes 5 other components:
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\itemize{
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\item{y2cMap:} {An input \code{y2cMap}.}
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\item{SigmaE:} {An input \code{SigmaE}.}
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\item{betastderrlist:} {An \code{fd} object estimating the standard
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errors of \code{betaestlist}.}
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\item{bvar:} {A covariance matrix for regression coefficient estimates.}
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\item{c2bMap:} {A mapping matrix that maps variation in Cmat to variation
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in regression coefficients.}
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}
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}
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\code{fRegress} with the following components:
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\itemize{
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\item{y:} {The first argument in the call to \code{fRegress}.
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This argument is coerced to \code{class} \code{fd} in fda version 5.1.9.
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Prior versions of the package converted it to an \code{fdPar}, but the
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extra structures in that class were not used in any of the
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\code{fRegress} codes.}
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\item{xfdlist:} {The second argument in the call to \code{fRegress}.}
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\item{betalist:} {The third argument in the call to \code{fRegress}.}
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\item{betaestlist:} {A list of length equal to the number of independent
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variables and with members having the same functional parameter
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structure as the corresponding members of \code{betalist}. These are the
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estimated regression coefficient functions.}
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\item{yhatfdobj:} {A functional parameter object (class \code{fdPar})
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if the dependent variable is functional or a vector if the dependent
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variable is scalar. This is the set of predicted by the
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functional regression model for the dependent variable.}
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\item{Cmatinv:} {A matrix containing the inverse of the coefficient
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matrix for the linear equations that define the solution to the
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regression problem. This matrix is required for function
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\code{fRegress.stderr} that estimates confidence regions
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for the regression coefficient function estimates.}
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\item{wt:} {The vector of weights input or inferred.}
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}
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If \code{class(y)} is numeric, the \code{fRegress} object also includes:
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\itemize{
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\item{df:} {The equivalent degrees of freedom for the fit.}
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\item{OCV} {the leave-one-out cross validation score for the model.}
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\item{gcv:} {The generalized cross validation score.}
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}
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If \code{class(y)} is \code{fd} or \code{fdPar}, the
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\code{fRegress} object returned also includes 5 other components:
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\itemize{
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\item{y2cMap:} {An input \code{y2cMap}.}
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\item{SigmaE:} {An input \code{SigmaE}.}
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\item{betastderrlist:} {An \code{fd} object estimating the standard
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errors of \code{betaestlist}.}
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\item{bvar:} {A covariance matrix for regression coefficient estimates.}
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\item{c2bMap:} {A mapping matrix that maps variation in Cmat to variation
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in regression coefficients.}
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}
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}
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\item{The model specification object case:}{The
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\code{fRegress.formula} and \code{fRegress.character} functions translate
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the \code{formula} into the argument list required by \code{fRegress.fdPar}
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or \code{fRegress.numeric}. With the default value 'fRegress' for the
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argument \code{method}, this list is then used to call the appropriate
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other \code{fRegress} function.}
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\code{fRegress.formula} and \code{fRegress.character} functions translate
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the \code{formula} into the argument list required by \code{fRegress.fdPar}
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or \code{fRegress.numeric}. With the default value 'fRegress' for the
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argument \code{method}, this list is then used to call the appropriate
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other \code{fRegress} function.}
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}
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Alternatively, to see how the \code{formula} is translated, use
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the alternative 'model' value for the argument \code{method}. In
@@ -283,9 +282,9 @@ fRegress(y, ...)
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\code{formula}. This will differ from \code{xfdlist} for
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any categorical or multivariate right hand side object.}
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\item{type:} {the \code{type} component of any \code{fd} object on the
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right hand side of \code{formula}.}
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right hand side of \code{formula}.}
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\item{nbasis:} {A vector containing the \code{nbasis} components of
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variables named in \code{formula} having such components.}
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variables named in \code{formula} having such components.}
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\item{xVars:} {An integer vector with all the variable names on the right
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hand side of \code{formula} containing the corresponding
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number of variables in \code{xfdlist}. This can exceed 1 for

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