@@ -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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-
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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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