basicTrendline2: an R package for adding trendline of basic regression models to plot

Authors

Weiping MEI https://PhDMeiwp.github.io

Graduate School of Fisheries and Environmental Sciences, Nagasaki University

Installation

Or the development version from github:

install.packages("devtools")
devtools::install_github("PhDMeiwp/basicTrendline2@master", force = TRUE)

Description

Plot and show both regression line and equation as simple as possible, by using different models built in the 'trendline()' function. The function includes the following models in the latest version:

"line2P" (formula as: y=a*x+b), "line3P" (y=a*x²+b*x+c), "log2P" (y=a*ln(x)+b), "exp2P" (y=a*e^b*x), "exp3P" (y=a*e^b*x+c), "power2P" (y=a*x^b), and "power3P" (y=a*x^b+c).

Besides, the summarized results of each fitted model are also output by default.

Usage

trendline2(x, y, model = "line2P", Pvalue.corrected = TRUE, linecolor = "red", lty = 1, lwd = 1,
			summary = TRUE, ePos = "topleft", eDigit = 5, eSize = 1,
			plot = TRUE, ...)

Arguments

x, y
the x and y arguments provide the x and y coordinates for the plot. Any reasonable way of defining the coordinates is acceptable.

model
select which model to fit. Default is "line2P". The "model" should be one of c("line2P", "line3P", "log2P", "exp3P", "power3P"), their formulas are as follows:
"line2P": y=a*x+b
"line3P": y=a*x²+b*x+c
"log2P": y=a*ln(x)+b
"exp2P": y=a*e^b*x
"exp3P": y=a*e^b*x+c
"power2P": y=a*x^b
"power3P": y=a*x^b+c

Pvalue.corrected
if P-value corrected or not, the vlaue is one of c("TRUE", "FALSE").

linecolor
color of regression line.

lty
line type. lty can be specified using either text c("blank","solid","dashed","dotted","dotdash","longdash","twodash") or number c(0, 1, 2, 3, 4, 5, 6). Note that lty = "solid" is identical to lty=1.

lwd
line width. Default is 1.

summary
summarizing the model fits. Default is TRUE.

ePos
equation position, such as one of c("none","bottomright","bottom","bottomleft","left","topleft","top","topright","right","center").

eDigit
the numbers of digits for equation parameters. Default is 5.

eSize
font size in percentage of equation. Default is 1.

plot
draw a scatter plot automatically, the vlaue is one of c("TRUE", "FALSE").

...
additional parameters to plot,such as type, main, sub, xlab, ylab, col.

Details

The linear models (line2P, line3P, log2P) in this package are estimated by lm function, while the nonlinear models (exp2P, exp3P, power2P, power3P) are estimated by nls function (i.e., least-squares method).
The argument 'Pvalue.corrected' is workful for non-linear regression only.
If "Pvalue.corrected = TRUE", the P-vlaue is calculated by using "Residual Sum of Squares" and "Corrected Total Sum of Squares (i.e. sum((y-mean(y))^2))".
If "Pvalue.corrected = TRUE", the P-vlaue is calculated by using "Residual Sum of Squares" and "Uncorrected Total Sum of Squares (i.e. sum(y^2))".

Value

R², indicates the R-Squared value of each regression model.

p, indicates the p-value of each regression model.

AIC or BIC, indicate the Akaike's Information Criterion or Bayesian Information Criterion for fitted model. Click AIC for details. The smaller the AIC or BIC, the better the model.

Examples

Then upload your dataset including x and y data, for example

x<-c(1,30,90,180,360)
y<-c(4,8,10,11,11)

[case 1] plot and add trendline as default:

library(basicTrendline2)

trendline2(x,y,model="exp3P", summary=TRUE, eDigit=3, ePos="bottom",linecolor="red")  

[case 2] plot and add trendline separately:

plot(x,y,yaxt="n",xlab = "your own xaxis name (mg)", ylab = "ylab (‰)")
axis(2,las=2)  # Change the y-axis text direction

library(basicTrendline)
#set plot=FALSE in the following codes
trendline2(x,y, plot=FALSE, model="power3P", summary=TRUE, eDigit=3, ePos="bottom",linecolor="black") 

[case 3] chanage other models, using the same function "trendline()"

library(basicTrendline2)

# change model to "log2P"
trendline2(x,y, model="log2P", summary=TRUE, eDigit=3, ePos="bottom",linecolor="black") 

“model” can be one of c('lin2P','line3P','log2P','exp3P','power3P')

• "line2P" # y=a*x+b

• "line3P" # y=a*x^2+b*x+c

• "log2P" # y=a*ln(x)+b

• "exp3P" # y=a*exp(b*x)+c

• "power3P" # y=a*x^b+c)

[case 4] draw different regression lines for the same dataset:

x1<-1:5
y1<-c(2,14,18,19,20)

plot(x1,y1,main="Different regression lines in one plot")

library(basicTrendline2)

trendline2(x1,y1,model="line2P",plot=FALSE,ePos="none",linecolor="red")
trendline2(x1,y1,model="log2P",plot=FALSE,ePos="none",linecolor="blue",lty=2)
trendline2(x1,y1,model="exp3P",plot=FALSE,ePos="none",linecolor="black",lty=3)

legend("bottomright",c("line2P","log2P","exp3P"), lty=c(1,2,3),col=c("red","blue","black"))

[case 5] draw trendlines by the same model (e.g. "exp3P") with different datasets:

import some datasets:

x1<- c(1,30,90,180,360)
x2<- c(1,45,90,180,360)
x3<- c(1,30,60,120,240)

y1<-c(10,14,18,19,20)    
y2<- c(8,11,13,15,17) 
y3<-c(9,13,16,16,16)   

Plot (or points) and add trendlines:

plot(x1,y1,,pch=1,col="red",xlim = c(0,400),ylim = c(6,22),main="Same regression lines with different datasets",xlab = "Time (days)", ylab = "your ylab (‰)")

points(x2,y2,pch=2,col="blue")  # pch values refer to different type for points
points(x3,y3,pch=3,col="green")

library(basicTrendline2)

# different linecolor and lty (lineType) for each trendline
trendline2(x1,y1,model="exp3P",linecolor="red",lty=1,plot=FALSE,ePos="none",summary = TRUE)->output1
trendline2(x2,y2,model="exp3P",linecolor="blue",lty = 2,plot=FALSE,ePos="none",summary = TRUE)->output2
trendline2(x3,y3,model="exp3P",linecolor="green",lty = 3,plot=FALSE,ePos="none",summary = TRUE)->output3

# add legend
legend("bottomright",c("x1y1","x2y2","x3y3"),pch=c(1,2,3), lty=c(1,2,3),col=c("red","blue","green"))

## return the results of each trendline as follow:
output1
output2
output3

[case 6] draw trendlines by using geom_trendline() function:

The values of each parameter of regression model can be found by typing 'trendline(x,y,model="log2P")' fuction in this pacakge.

library(basicTrendline2)
x <- 1:5
y <- c(2,14,18,19,20)
xy <- data.frame(x, y)

gg <- ggplot(aes(x,y), data = xy) + geom_point()
gg + geom_trendline(model = "log2P", color = "blue")

Contributions

R codes contributed by

• adding-regression-line-equation-and-r2-on-graph-1: http://blog.sciencenet.cn/blog-267448-1021594.html
• adding-regression-line-equation-and-r2-on-graph-2: https://stackoverflow.com/questions/7549694/adding-regression-line-equation-and-r2-on-graph
• What is non-linear regression?: https://datascienceplus.com/first-steps-with-non-linear-regression-in-r/
• adding regression line for nonlinear regression: http://blog.sciencenet.cn/blog-651374-1014133.html
• R codes for 'print.summary.nls of exp3P and power3P' cite from https://github.com/SurajGupta/r-source/blob/master/src/library/stats/R/nls.R
• and so on...

Contact

• Bugs and feature requests can be filed to https://github.com/PhDMeiwp/basicTrendline2/issues. BTW, Pull requests are also welcome.