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Published in:
2019 | OriginalPaper | Chapter
2. Multivariate Data Visualization
Authors : Matt Wiley, Joshua F. Wiley
Published in: Advanced R Statistical Programming and Data Models
Publisher: Apress
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Abstract
The previous chapter covered methods for univariate data visualization. This chapter continues that theme, but moves from visualizing single variables to visualizing multiple variables at a time. In addition to examining distributions and anomalous values as in the previous chapter, we also cover how to visualize the relations between variables. Visualizing relations between variables can help particularly for more traditional statistical models where the data analyst must specify the functional form (e.g., linear, quadratic, etc.). In later chapters we will also cover machine learning models that employ algorithms to learn the functional form in data without the analyst needing to specify it.
library(checkpoint)
checkpoint("2018-09-28", R.version = "3.5.1",
project = book_directory,
checkpointLocation = checkpoint_directory,
scanForPackages = FALSE,
scan.rnw.with.knitr = TRUE, use.knitr = TRUE)
library(knitr)
library(ggplot2)
library(cowplot)
library(MASS)
library(mvtnorm)
library(mgcv)
library(quantreg)
library(JWileymisc)
library(data.table)
options(width = 70, digits = 2)