ggtrendline: an R package for adding trendline and confidence interval to ggplot

1. Installing "ggtrendline" package in R

Get the released version from CRAN:
```
  install.packages("ggtrendline")
```

Or the development version from Github:

  install.packages("devtools")
  devtools::install_github("PhDMeiwp/ggtrendline@master", force = TRUE)
  library(ggtrendline)

2. Using "ggtrendline" package

 library(ggplot2)
 library(ggtrendline)
 x <- c(1, 3, 6, 9,  13,   17)
 y <- c(5, 8, 11, 13, 13.2, 13.5)

2.1 default ("line2P")

 ggtrendline(x, y, model = "line2P")

2.2 add geom_point()

 ggtrendline(x, y, model = "line3P") + geom_point(aes(x, y)) + theme_bw()

2.3 CI lines only, without CI filling

 ggtrendline(x, y, model = "log2P", CI.fill = NA) + 
		geom_point(aes(x, y))+ theme_classic()

2.4 set the regression line and geom_point()

 ggtrendline(x, y, model = "exp2P", linecolor = "blue", linetype = 1, linewidth = 1) + 
         geom_point(aes(x, y), color = "blue", shape = 1, size = 3)

2.5 set confidence interval

 ggtrendline(x, y, model = "exp3P", CI.level = 0.99, 
            CI.fill = "red", CI.alpha = 0.1, CI.color = NA, CI.lty = 2, CI.lwd = 1.5) + 
         geom_point(aes(x, y))

2.6 one trendline with different points belonged to multiple groups.

	library(ggplot2)
	library(ggtrendline)
	data("iris")
	x <- iris$Petal.Width
	y <- iris$Petal.Length
	group <- iris$Species
	ggtrendline(x,y,"exp3P") + geom_point(aes(x,y,color=group))

3. Details

3.1 Description

The 'ggtrendline' package is developed for adding trendline and confidence interval of linear or nonlinear regression model, and showing equation, R square, and P value to 'ggplot' as simple as possible.

For a general overview of the methods used in this package, see Ritz and Streibig (2008) doi:10.1007/978-0-387-09616-2 and Greenwell and Schubert Kabban (2014) doi:10.32614/RJ-2014-009.

3.2 ggtrendline function

The built-in 'ggtrendline()' function includes the following models:

"line2P", formula as: y = a*x + b;
"line3P", y = a*x^2 + b*x + c;
"log2P" , y = a*ln(x) + b;
"exp2P", y = a*exp(b*x);
"exp3P", y = a*exp(b*x) + c;
"power2P", y = a*x^b;
"power3P", y = a*x^b + c.

3.3 stat_eq and stat_rrp functions

The built-in 'stat_eq()' and 'stat_rrp()' functions can be used separately, i.e., not together with 'ggtrendline()' function.

To see more details, you can run the following R code if you have the "ggtrendline" package installed:

library(ggtrendline)
?ggtrendline
?stat_eq
?stat_rrp

4. Contact

Bugs and feature requests can be filed to https://github.com/PhDMeiwp/ggtrendline/issues.
BTW, Pull requests are also welcome.

5. Acknowledgements

We would like to express our special thanks to Uwe Ligges, Gregor Seyer, and CRAN team for their valuable comments to the 'ggtrendline' package.