geom_abline : Add regression lines A simplified format of the functiongeom_abline()is : geom_abline(intercept, slope, linetype, color, size) The functionlm()is used to fit linear models. # Fit regression line require(stats) reg<-lm(mpg ~ wt, data = mtcars) reg ...
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...
("a", "a", "b", "b")) Fit polynomial regression line and add labels: # Polynomial regression. Sow equation and adjusted R2 formula <- y ~ poly(x, 3, raw = TRUE) p <- ggplot(my.data, aes(x, y2, color = group)) + geom_point() + geom_smooth(aes(fill = group), method...
Scatter plot with linear regression line of best fit 图1,显示不同类别 df <- ggplot2::mpg %>% setDT() df_select <- df[cyl %in% c(4,8),] %>% .[,cyl:=as.factor(cyl)] cyl_color <- c("#1f77b4", "#ff983e") # geom_smooth的填充范围,只有数据和全图可选,而且se只会按垂直方向...
lm_fit <- lm(y ~ x, data = df) #with regression line ggplot(df, mapping = aes(x=x, y=y)) + geom_point(color="blue") + geom_smooth(method='lm', se=FALSE, color="red") 我想要插入像这样的密度曲线(只是朝相反方向):
#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),...
#Scatterplots(sp)sp<-ggscatter(mtcars,x="wt",y="mpg",add="reg.line",#Addregressionline=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 ...
(955)# Make some noisily increasing datadat<-data.frame(cond=rep(c("A","B"),each=10),xvar=1:20+rnorm(20,sd=3),yvar=1:20+rnorm(20,sd=3))p<-ggplot(dat,aes(x=xvar,y=yvar))+geom_point(shape=1)+# Use hollow circlesgeom_smooth(method=lm)# Add linear regression linefig<-...
线(line,vline,abline,hline,stat_function等):一般是基于函数来处理位置 射(segment):特征是指定位置有xend和yend,表示射线方向 面(tile, rect):这类一般有xmax,xmin,ymax,ymin指定位置 棒(boxplot,bin,bar,histogram):往往是二维或一维变量,具有width属性 ...