#' Implements simple linear regression by gradient descent
#'
#' @param dat A data frame
#' @param response The name of a response variable in the data frame (unquoted)
#' @param explanatory The name of the explanatory variable in the data frame (unquoted)
#'
#' @return A data frame of coefficients
#'
#' @import dplyr
#'
#' @export
slr_gd <- function(dat, response, explanatory){
### Compute coefficients by gradient descent
### Return a data frame of the same form as in the `simple_linear_regression`
return(results)
}
#' Implements linear regression with many predictors by gradient descent
#'
#' This function computes coefficients for multiple regression by gradient descent
#' All columns of the provided data frame are used as predictors, except the
#' one specified as a response.
#'
#' No interaction terms are included.
#'
#'
#' @param dat A data frame
#' @param response The name of a response variable in the data frame (unquoted)
#'
#' @return A data frame of coefficients
#'
#' @import dplyr
#'
#'@export
mlr_gd <- function(dat, response) {
### Compute coefficients by gradient descent
### Return a data frame of the same form as in the `multiple_linear_regression`
return(results)
}
#' Implements linear regression with many predictors by matrix decomposition
#'
#' This function computes coefficients for multiple regression by QR matrix decomposition
#' All columns of the provided data frame are used as predictors, except the
#' one specified as a response.
#'
#' No interaction terms are included.
#'
#'
#' @param dat A data frame
#' @param response The name of a response variable in the data frame (unquoted)
#'
#' @return A data frame of coefficients
#'
#' @import dplyr
#'
#'@export
mlr_qr <- function(dat, response) {
### Compute coefficients by QR decomposition
### Return a data frame of the same form as in the `multiple_linear_regression`
return(results)
}
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