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Dhanush Kumar Reddy Narayana Reddy
Group5Labbonus
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a49d9d3e
Commit
a49d9d3e
authored
4 months ago
by
Dhanush Kumar Reddy Narayana Reddy
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DESCRIPTION
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DESCRIPTION
NAMESPACE
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NAMESPACE
R/ridgereg.R
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R/ridgereg.R
man/fun.Rd
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man/fun.Rd
man/ridgereg-class.Rd
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man/ridgereg-class.Rd
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DESCRIPTION
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Package: group5labbonus
Package: group5labbonus
Type: Package
Type: Package
Title:
What the Package Does (Short Line)
Title:
Ridge Regression Analysis in R
Version: 1.0
Version: 1.0
Date: 2024-11-03
Date: 2024-11-03
Author:
Who wrote it
Author:
Manu Jain [aut], Dhanush Kumar Reddy Narayana Reddy [cre]
Maintainer:
Who to complain to <yourfault@somewhere.net
>
Maintainer:
Dhanush Kumar Reddy Narayana Reddy to <dhana004@student.liu.se
>
Description: More about what it does (maybe more than one line).
Description: More about what it does (maybe more than one line).
License: GPL-3 + file LICENSE
License: GPL-3 + file LICENSE
Imports:
methods
RoxygenNote: 7.3.2
RoxygenNote: 7.3.2
Encoding: UTF-8
Encoding: UTF-8
Suggests:
Suggests:
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NAMESPACE
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# Generated by roxygen2: do not edit by hand
# Generated by roxygen2: do not edit by hand
export(ridgereg)
export(ridgereg)
importFrom(methods,new)
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R/ridgereg.R
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#' @field coefficients A matrix containing the estimated ridge regression coefficients.
#' @field coefficients A matrix containing the estimated ridge regression coefficients.
#' @field fitted_values A matrix of the fitted (predicted) values.
#' @field fitted_values A matrix of the fitted (predicted) values.
#' @field residuals A matrix of the residuals (difference between actual and fitted values).
#' @field residuals A matrix of the residuals (difference between actual and fitted values).
#'
#'
@method initialize Initializes
#' @param formula A formula specifying the model.
#' @param formula A formula specifying the model.
#' @param data A data frame containing the variables in the formula.
#' @param data A data frame containing the variables in the formula.
#' @param lambda The ridge penalty parameter.
#' @param lambda The ridge penalty parameter.
#'
#'
#' @method print Prints
#'
#' @method predict Predicts
#' @param newdata A data frame for which to predict new values.
#' @return A vector of predicted values.
#'
#' @method coef Extracts
#' @return A named vector of the regression coefficients.
#' @importFrom methods new
#' @export ridgereg
#' @export ridgereg
ridgereg
<-
setRefClass
(
ridgereg
<-
setRefClass
(
"ridgereg"
,
"ridgereg"
,
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\name{fun}
\alias{fun}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
A Capitalized Title (ideally limited to 65 characters)
}
\description{
%% ~~ A concise (1-5 lines) description of what the function does. ~~
}
\usage{
fun()
}
%- maybe also 'usage' for other objects documented here.
\details{
%% ~~ If necessary, more details than the description above ~~
}
\value{
%% ~Describe the value returned
%% If it is a LIST, use
%% \item{comp1 }{Description of 'comp1'}
%% \item{comp2 }{Description of 'comp2'}
%% ...
}
\references{
%% ~put references to the literature/web site here ~
}
\author{
%% ~~who you are~~
}
\note{
%% ~~further notes~~
}
%% ~Make other sections like Warning with \section{Warning }{....} ~
\seealso{
%% ~~objects to See Also as \code{\link{help}}, ~~~
}
\examples{
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or standard data sets, see data().
## The function is currently defined as
function ()
print()
}
% Add one or more standard keywords, see file 'KEYWORDS' in the
% R documentation directory (show via RShowDoc("KEYWORDS")):
% \keyword{ ~kwd1 }
% \keyword{ ~kwd2 }
% Use only one keyword per line.
% For non-standard keywords, use \concept instead of \keyword:
% \concept{ ~cpt1 }
% \concept{ ~cpt2 }
% Use only one concept per line.
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man/ridgereg-class.Rd
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\item{data}{A data frame containing the variables in the formula.}
\item{data}{A data frame containing the variables in the formula.}
\item{lambda}{The ridge penalty parameter.}
\item{lambda}{The ridge penalty parameter.}
\item{newdata}{A data frame for which to predict new values.}
}
\value{
A vector of predicted values.
A named vector of the regression coefficients.
}
}
\description{
\description{
This class implements ridge regression with methods for initialization, coefficient extraction,
This class implements ridge regression with methods for initialization, coefficient extraction,
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