ggplot2 ggplot() 分组回归，分组填充柱形图，设置stat_xxx，增添残差回归图层

dplot <- ggplot(diamonds, aes(clarity, fill = cut)) ##按cut类 计数填充
dplot + geom_bar(position = "stack")##条形图 分类
dplot + geom_bar(position = "fill")##等高条形图
dplot + geom_bar(position = "dodge")##并排分类条形图

p <- ggplot(Oxboys, aes(age, height, group = Subject)) + 
  geom_line()

p + geom_smooth(aes(group = Subject), method="lm", se = F)

p + geom_smooth(aes(group = 1), method="lm", size = 2, se = F)

#########################上下相同######################

qplot(age, height, data=Oxboys, group = Subject, geom="line") +
  geom_smooth(method="lm", se = F)
qplot(age, height, data=Oxboys, group = Subject, geom="line") +
  geom_smooth(aes(group = 1), method="lm", size = 2, se = F)
####################################################

qplot(Occasion, height, data=Oxboys, geom="boxplot")
qplot(Occasion, height, data=Oxboys, geom="boxplot") +
 geom_line(aes(group = Subject), colour="#3366FF") #######叠加图层


d <- ggplot(diamonds, aes(carat)) + xlim(0, 3)
d + stat_bin(aes(ymax = ..count..), binwidth = 0.1, geom = "area")
d + stat_bin(
  aes(size = ..density..), binwidth = 0.1, 
  geom = "point", position="identity"
)

stat_bin is suitable only for continuous x data. If your x data is discrete, you probably want to use stat_count.

p <- ggplot(diamonds,aes(carat)) + xlim(0, 3)

p + geom_histogram(position = 'identity',
                   alpha=0.5,
                   aes(y = ..density..,
                       fill = factor(color))) +
  stat_density(geom = 'line',
               position = 'identity',
               aes(colour = factor(color)))

　　

model <- lme(height ~ age, data = Oxboys, 
 random = ~ 1 + age | Subject)
oplot <- ggplot(Oxboys, aes(age, height, group = Subject)) + 
  geom_line()

age_grid <- seq(-1, 1, length = 10)
subjects <- unique(Oxboys$Subject)

preds <- expand.grid(age = age_grid, Subject = subjects) ##扩充data frame 形成完整的
preds$height <- predict(model, preds)

oplot + geom_line(data = preds, colour = "#3366FF", size= 0.4)

Oxboys$fitted <- predict(model) ##向Oxboys里添加fitted列
Oxboys$resid <- with(Oxboys, fitted - height) ##with 内调data，后边是进行相应的变量操作

oplot %+% Oxboys + aes(y = resid) + geom_smooth(aes(group=1)) ##同样的oplot采用不同的数据绘图，并更改图层设置，height变为resid 残差，并增添总体回归线