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"...
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",...
# Scatter Plotlibrary(ggplot2)ggplt<-ggplot(Orange,aes(x=circumference,y=age))+geom_point()+theme_classic()ggplt# Plotting a single Regression Lineggplt+geom_smooth(method=lm,se=FALSE,fullrange=TRUE) R Copy 输出 这是一个单一的平滑线,或俗称为回归线。在这里,各点是结合在一起的,没有在任...
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...
() # 选择子集数据 subset_data <- subset(your_data, condition) # 为子集数据创建回归线 p <- p + geom_smooth(data = subset_data, method = "lm", se = TRUE) # 添加标题和轴标签 p <- p + labs(title = "Regression Line for Subset Data", x = "X Variable", y = "Y Var...
# Fit regression linerequire(stats)reg<-lm(mpg~wt,data=mtcars)reg coeff<-coefficients(reg)# Equation of the line :eq<-paste0("y = ",round(coeff[2],1),"*x + ",round(coeff[1],1))# Plotsp+geom_abline(intercept=37,slope=-5)+ggtitle(eq)# Change line type, color and sizesp+geo...
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 复制Cloud Studio 代码运行 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...
#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)+ ...
(mtcars, x = "wt", y = "mpg", add = "reg.line", # Add regression line conf.int = 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 = ...
#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 ...