In yewei369/FancyPackRLiU4: LiUR3-RC

knitr::opts_chunk$set(error = TRUE)
library(FancyPackRLiU4)
#install.packages("ggplot2")
library("png")
library("grid")
library("ggplot2")

Description

linreg is a pilot RC project to carry out linear regression. Given \code{formula} and data source \code{data}, it will find the best fitted linear regression model.

Fields

formula, a suggested linear regression model

data, a data source used to train the model

guo, a list of key results from regression, including Coefficients, FittedValues, Residuals, FreedomDegree, VarianceResiduals, StdErrorResiduals, VarianceCoefficients, StdError, Tcoefficients, Possibility, X, Y, Formula, Data, VariableNames.

Methods

print() print out the coefficients and coefficient names, similar as done by the lm class

plot() plot the following two plots using ggplot2. Remember to include ggplot2 in your package

resid() return the vector of residuals

pred() return the predicted values

coef() return the coefficients as a named vector

summary() return a printout including the coefficients with their standard error, t-value and p-value as well as the standard error of residuals and the degrees of freedom in the model.

Examples

data(iris)
a<-linreg$new(formula=Sepal.Length~Sepal.Width,data=iris)
a$print()          
a$plot()
a$resid()
a$pred()
a$coef()
a$summary()

yewei369/FancyPackRLiU4 documentation built on Nov. 5, 2019, 12:34 p.m.