#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), label.x = 3) #Add correlation coefficientsp ...
复制 #Scatterplots(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),label.x=3)#Add correlation c...
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 复制 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曲线 代码语言:javascript 复制...
geom_smooth(method=lm, # Add linear regression line se=FALSE) # Don't add shaded confidence region 4.3、散点图添加置信区间区域 ggplot(dat, aes(x=xvar, y=yvar)) + geom_point(shape=1) + # Use hollow circles geom_smooth(method=lm) # Add linear regression line # (by default includes ...
# Add the regression line ggplot(mtcars, aes(x=wt, y=mpg)) + geom_point()+ geom_smooth(method=lm) # Remove the confidence interval ggplot(mtcars, aes(x=wt, y=mpg)) + geom_point()+ geom_smooth(method=lm, se=FALSE) # Loess method ...
# 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...
Scatter_plots <- ggscatter(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(col...
#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 ...
Scatter_plots <- ggscatter(mtcars, x = "wt", y = "mpg",add="reg.line",#Addregression lineconf.int=TRUE,#Addconfidence intervalcolor="cyl",palette="jco",# Colorbygroups"cyl"shape="cyl"# Change point shapebygroups"cyl")+stat_cor(aes(color = cyl), label.x = 3) # Add correlation...
("a", "a", "b", "b"))Fit polynomial regression line and add labels:# Polynomialregression. Sow equation and adjusted R2formula <- y ~ poly(x, 3, raw = TRUE)p <- ggplot(my.data, aes(x, y2, color = group)) + geom_point() + geom_smooth(aes(fill = group), method = "...