# Create example datarm(list=ls())set.seed(87)x<-rnorm(250)y<-rnorm(250)+2*x data<-data.frame(x,y)# Print first rows of datahead(data)# Install & load ggplot2library("ggplot2")# Create basic ggplot# and Add regression lineggp<-ggplot(data,aes(x,y))+geom_point()ggp ggp+sta...
利用geom_smooth()添加回归线 # 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",...
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...
p3 p4 <- p + geom_smooth(method = "lm", se = FALSE) #no the confidence interval band p4 #(3)多项式回归 p5 <- ggplot(mtcars, aes(qsec, hp)) + geom_point() + geom_smooth(method = "lm", formula = y ~ poly(x, 2)) #polynomial regression line 多项式回归 这里是二次多项式 p5...
# loess method: local regression fitting p3 <- ggscatter(df, x = "wt", y = "mpg", add = "loess", conf.int = TRUE, cor.coef = TRUE, # Add correlation coefficient. see ?stat_cor cor.coeff.args = list(method = "spearma...
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
#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 ...