<Ways to draw some famous distributions using curve(), ggplot()>
1. exponential distribution
> curve(dexp(x,rate=2),from=0,to=6) |
>ggplot(data.frame(x=c(0,6)),aes(x=x))+stat_function(fun=dexp,args=list(rate=2)) |
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2. Normal distribution
> curve(dnorm(x,mean=5,sd=1),from=-10,to=10) |
>ggplot(data.frame(x=c(-10,10)),aes(x=x))+stat_function(fun=dnorm,args=list(mean=5,sd=1)) |
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3. T distribution
>curve(dt(x,df=3),from=0,to=10) |
>ggplot(data.frame(x=c(0,10)),aes(x=x))+stat_function(fun=dt,args=list(df=3)) |
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4. Gamma distribution
> curve(dgamma(x,shape=5,scale=2),from=0,to=10) |
>ggplot(data.frame(x=c(0,10)),aes(x=x))+stat_function(fun=dgamma,args=list(shape=5,scale=2)) |
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5. Beta distribution
> curve(dbeta(x,shape1=2,shape2=5),from=0,to=1) |
>ggplot(data.frame(x=c(0,1)),aes(x=x))+stat_function(fun=dbeta,args=list(shape1=2,shape2=5)) |
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<Ways to make a new curve using curve(), ggplot()>
> A<-function(x){1/(x^2+9)} > curve(A(x),from=0, to=10) |
> A<-function(x){1/(x^2+9)} >ggplot(data.frame(x=c(0,10)),aes(x=x))+stat_function(fun=A,geom="line") |
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<Ways to make curves in a graph using curve()>
For this case, the way to make curves in a graph is to use curve() function three times with different parameters and colors for each other.
You should recognize that x-axis and y-axis of the graph is determined by the curve() function.
That is the reason why the first graph has y-axis from 0 to 5 and the second graph has y-axis from 0 to 50.
> curve(dexp(x,rate=5),from=0,to=3) > curve(dexp(x,rate=20),add=TRUE,col="red") > curve(dexp(x,rate=50),add=TRUE,col="blue") |
> curve(dexp(x,rate=50),from=0,to=3) > curve(dexp(x,rate=20),add=TRUE,col="red") > curve(dexp(x,rate=50),add=TRUE,col="blue") |
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<Ways to make curves in a graph using ggplot()>
>ggplot(data.frame(x=c(0,3)),aes(x=x))+stat_function(fun=dexp,args=list(rate=5))+stat_function(fun=dexp,args=list(rate=20),col="red")+stat_function(fun=dexp,args=list(rate=50),col="blue")
