In BangyaoZhao/package2:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Introduction

In statistics, linear regression is a linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). linear regression allows users to:

1. Fit linear regression model with or without intercept and obtain the estimated coeficients.
2. Obtain estimated y's.
3. Obtain sum of squares.
4. Obtain the t and f statistics and p values.
5. Obtain the hat matrix.
6. Obtain residuals.

Install the package

linear regression is a package for R, so you need R first. We also strongly recommend the RStudio integrated development environment as a user-friendly graphical wrapper for R.

linear regression is now available on github, use the following code to install linear regression.

Heading 3

1

# A comment
library(package2)

1+1
linear_regression(c(3,5),c(1,2))$coefs

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BangyaoZhao/package2 documentation built on Nov. 21, 2019, 3:55 a.m.