data<-data.frame(x,y)reg<-lm(formula=y~x,data=data)#get intercept and slope valuecoeff<-coefficients(reg)intercept<-coeff[1]slope<-coeff[2]# Create basic ggplotggp<-ggplot(data,aes(x,y))+geom_point()# add the regression lineggp+geom_abline(intercept=intercept,slope=slope,color="red"...
https://stackoverflow.com/questions/7549694/add-regression-line-equation-and-r2-on-graph 首先是模拟一份数据集 代码语言:javascript 代码运行次数:0 运行 AI代码解释 df<-data.frame(x = c(1:100)) df$y <- 2 + 3 * df$x + rnorm(100, sd = 40) head(df) ggplot2基本的散点图并添加拟合...
https://stackoverflow.com/questions/49418552/adding-regression-line-equation-and-r2-on-separate-lines-graph https://stackoverflow.com/questions/37494969/ggplot2-add-regression-equations-and-r2-and-adjust-their-positions-on-plot
conf.int = TRUE, # Add confidence interval cor.coef = TRUE, # Add correlation coefficient. see ?stat_cor cor.coeff.args = list(method = "pearson", label.x = 3, label.sep = "\n") ) p2 1 2 3 4 5 6 7 # loess method...
#Scatter plots(sp)sp <- ggscatter(mtcars, x="wt", y="mpg",add="reg.line",#Add regressionlineconf.int= TRUE,#Add confidence intervalcolor ="cyl", palette ="jco",#Color by group cylshape ="cyl"#Change point shape by groups cyl)+ ...
#Scatter plots(sp)sp <- ggscatter(mtcars, x="wt", y="mpg", add = "reg.line", #Add regression line conf.int = TRUE, #Add confidence interval color = "cyl", palette = "jco",#Color by group cyl shape = "cyl" #Change point shape by groups cyl )+ stat_cor(aes(color=cyl), ...
add = "reg.line", # Add regression line = TRUE, # Add confidence interval color = "cyl", palette = "jco", # Color by groups "cyl" shape = "cyl" # Change point shape by groups "cyl" )+ stat_cor(aes(color = cyl), label.x = 3) # Add correlation coefficient sp ### 以下三...
#Scatterplots(sp)sp<-ggscatter(mtcars,x="wt",y="mpg",add="reg.line",#Add regression line conf.int=TRUE,#Add confidenceintervalcolor="cyl",palette="jco",#Colorbygroupcylshape="cyl"#Change point shape by groups cyl)+stat_cor(aes(color=cyl),label.x=3)#Add correlation coefficientsp ...
# Load the ggplot2 package library(ggplot2) # Create a scatterplot ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() # Add a regression line ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + geom_smooth(method = "lm", color = "red", linetype = "dashed", size...
Add regression line, correlation coefficient and equantions of the fitted line. Key functions: stat_smooth()[ggplot2] stat_cor()[ggpubr] stat_poly_eq()[ggpmisc]formula <- y ~ xp + stat_smooth( aes(color = Species, fill = Species), method = "lm") + stat_cor(aes(color = Species...