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",...
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...
# Scatter Plot library(ggplot2) ggplt <- ggplot(Orange,aes(x=circumference,y=age))+ geom_point()+ theme_classic() ggplt # Plotting a single Regression Line ggplt+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...
Add regression line, correlation coefficient and equantions of the fitted line. Key functions: stat_smooth()[ggplot2] stat_cor()[ggpubr] stat_poly_eq()[ggpmisc] 代码语言:javascript 代码运行次数:0 运行 AI代码解释 formula<-y~x p+stat_smooth(aes(color=Species,fill=Species),method="lm")+...
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from statsmodels.sandbox.regression.predstd import wls_prediction_std from statsmodels.stats.outliers_influence import summary_table import scipy.stats as stats import datetime date_types=(Timestamp, #需要添加的 #pd.tslib.Timestamp, #需要被注释掉的 pd.DatetimeIndex,pd.Period,pd.PeriodIndex,...
#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 = 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) # ...