用ggplot2制作fitdist情节

Question

我用包中的fitdist函数拟合了正态分布fitdistrplus.使用denscomp,qqcomp,cdfcomp和ppcomp我们就可以绘制histogram against fitted density functions,theoretical quantiles against empirical ones,the empirical cumulative distribution against fitted distribution functions,和theoretical probabilities against empirical ones分别为如下.

set.seed(12345)
df <- rnorm(n=10, mean = 0, sd =1)
library(fitdistrplus)
fm1 <-fitdist(data = df, distr = "norm")
summary(fm1)

denscomp(ft = fm1, legendtext = "Normal")

qqcomp(ft = fm1, legendtext = "Normal")

cdfcomp(ft = fm1, legendtext = "Normal")

ppcomp(ft = fm1, legendtext = "Normal")

我非常有兴趣制作这些fitdist情节ggplot2.MWE如下:

qplot(df, geom = 'blank') +
  geom_line(aes(y = ..density.., colour = 'Empirical'), stat = 'density') +  
  geom_histogram(aes(y = ..density..), fill = 'gray90', colour = 'gray40') +
  geom_line(stat = 'function', fun = dnorm, 
            args = as.list(fm1$estimate), aes(colour = 'Normal')) +
  scale_colour_manual(name = 'Density', values = c('red', 'blue'))

ggplot(data=df, aes(sample = df)) + stat_qq(dist = "norm", dparam = fm1$estimate)

如果有人给我提示制作这些fitdist情节,我将非常感激ggplot2.谢谢

Answer 1

你可以使用类似的东西：

library(ggplot2)

ggplot(dataset, aes(x=variable)) +
geom_histogram(aes(y=..density..),binwidth=.5, colour="black", fill="white") +
stat_function(fun=dnorm, args=list(mean=mean(z), sd=sd(z)), aes(colour =
"gaussian", linetype = "gaussian")) + 
stat_function(fun=dfun, aes(colour = "laplace", linetype = "laplace")) + 
scale_colour_manual('',values=c("gaussian"="red", "laplace"="blue"))+
scale_linetype_manual('',values=c("gaussian"=1,"laplace"=1))

您只需要dfun在运行图形之前进行定义。stat_function在此示例中，它是拉普拉斯分布，但您可以选择任何您想要的分布，并根据需要添加更多分布。