R/linear_regression.R

In mknauss58/Lab-6-Group: This is a sparse package for a Stat 431 assignment.

#' Implements simple linear regression by hand
#'
#' @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)
#' @param method The method used to compute the coefficients (NULL, "qr", "gradientdescent")
#'
#' @return A data frame of coefficients
#'
#' @import dplyr
#'
#' @export
simple_linear_regression <- function(dat, response, explanatory, method = NULL){

  x <- dat %>% pull({{explanatory}})
  y <- dat %>% pull({{response}})

  explan_name <- dat %>%
    select({{explanatory}}) %>%
    names()

  x_bar <- mean(x)
  y_bar <- mean(y)

  ### Edit code after here

  sd_x <- sd(x)
  sd_y <- sd(y)

  beta_1 <- cov(x,y)/(sd_x)^2
  beta_0 <-  y_bar - (x_bar*beta_1)

  ### Stop editing

  results <- tibble::tibble(
    Intercept = beta_0,
    Slope = beta_1
  )

  names(results)[2] <- explan_name

  return(results)

}


#' Implements linear regression with many predictors by hand
#'
#' This function computes coefficients for multiple regression by hand.
#' 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)
#' @param method The method used to compute the coefficients (NULL, "qr", "gradientdescent")
#'
#' @return A data frame of coefficients
#'
#' @import dplyr
#'
#'@export
multiple_linear_regression <- function(dat, response, method = NULL) {

  x <- dat %>% select(-{{response}})
  x <- as.matrix(x)
  int <- as.matrix(rep(1, nrow(x)), ncol = 1)
  x <- cbind(int, x)
  y <- dat %>% select({{response}})
  y <- as.matrix(y)

  results <- solve(crossprod(x)) %*% (t(x) %*% y)

  results <- as.data.frame(t(results))
  names(results)[1] <- "Intercept"

  return(results)

}