Regression analysis is a statistical process for estimating the relationship between two or more variables. The relationship is modeled as \(y \sim x\) or \(y = f(x)\). Both model descriptions indicate, that the variable \(y\) is a function of \(x\). Therefore, the variable \(y\) is denoted as the response variable or dependent variable, whereas the variable \(x\) is denoted as the predictor variable or independent variable.
The following functions and R-packages are used in this section (in alphabetical order):
R-packages
- caTools
Functions
- c()
- caTools::sample.split()
- cbind()
- ceiling()
- coef()
- confint.default()
- cooks.distance()
- cov()
- data()
- data.frame()
- dim()
- dfbetas()
- dffits()
- fitted()
- floor()
- hatvalues()
- list()
- lm()
- max()
- min()
- mean()
- nrow()
- paste0()
- poly()
- predict()
- rbind()
- read.csv()
- residuals()
- rnorm()
- round()
- runif()
- sample()
- seq()
- set.seed()
- sqrt()
- str()
- sum()
- summary()
- var()
- which()
- which.min()
Plotting Functions
- abline()
- legend()
- lines()
- matplot()
- par()
- plot()
- points()
- title()
Citation
The E-Learning project SOGA-R was developed at the Department of Earth Sciences by Kai Hartmann, Joachim Krois and Annette Rudolph. You can reach us via mail by soga[at]zedat.fu-berlin.de.
You may use this project freely under the Creative Commons Attribution-ShareAlike 4.0 International License.
Please cite as follow: Hartmann, K., Krois, J., Rudolph, A. (2023): Statistics and Geodata Analysis using R (SOGA-R). Department of Earth Sciences, Freie Universitaet Berlin.