例子 library(ggplot2)ggplt<-ggplot(Orange,aes(x=circumference,y=age,shape=Tree))+geom_point()+theme_classic()ggplt# Plotting multiple Regression Linesggplt+geom_smooth(method=lm,se=FALSE,fullrange=TRUE,aes(color=Tree)) R Copy 输出
(method = "lm", se = FALSE) + # 添加线性回归线层 labs(title = "Multiple Linear Regression Lines", x = "X Axis", y = "Y Axis") + # 添加标题和轴标签 theme_minimal() # 应用最小化主题 参考链接 ggplot2 官方文档 R Graphics Cookbook 遇到的问题及解决方法 问题:在拟合回归线时,发现...
其他有用的统计变化包括一维和二维的封箱(binning),求组平均(group means),分位数回归(quantile regression)和等高线(contouring)。 As well as adding an additional step to summarise the data, we also need some extra steps when we get to the scales. This is because we now have multiple datasets (f...
1 Multiple Regression lines in ggplot2 0 How to add linear lines to a plot with multiple data sets of a data frame? 1 How to add two linear fits to plot? 1 Plotting more than one linear regression line in ggplot 2 R - ggplot multiple regression lines for differen...
), # adds equation to linear regression label.x = 0, label.y = 400, size = 4) Also works well with facet_wrap() when you have multiple groups df$group <- rep(1:2,50) ggplot(data = df, aes(x = x, y = y)) + stat_smooth(method = "lm", se=FALSE, color="black", ...
text = c("This is text", "Text with\nmultiple lines", "Some more text") ) library(ggplot2) p <- ggplot(dat, aes(x=1, y=y)) + scale_y_continuous(limits=c(0.5, 3.5), breaks=NULL) + scale_x_continuous(breaks=NULL) p + geom_text(aes(label=text), family="Times", fontface...
superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression ...
stat_multcomp() Multiple comparisons (label_pairwise or text) those supported by glht (1, 2, 7)Notes: (1) weight aesthetic supported; (2) user defined fit functions that return an object of a class derived from lm are supported even if they override the statistic’s formula argument; (...
stat_multcomp()Multiple comparisons (label_pairwiseortext)those supported byglht(1, 2, 7) Notes: (1)weightaesthetic supported; (2) user defined fit functions that return an object of a class derived fromlmare supported even if they override the statistic’sformulaargument; (3) unlimited quant...
Beyond Multiple Linear Regression[52]:回归分析的拓展:广义线性模型和分层模型 Applied longitudinal data analysis in brms and the tidyverse[53]:纵向数据分析 Interpretable Machine Learning[54]:可解释机器学习 现代应用统计与R语言[55]:顾名思义 R语言教程[56]:同上 ...