I'm trying to write a function that proves the Central Limit Theorem in R. It will take a value n and a Probability Density Function as parameters, and returns the mean of 1000 samples of a PDF, n times.
So I have a PDF as a function, like this:
pdf1 <- function() {
x = runif(1, min=0, max=2)
if(x <= 1) {
y = x
} else {
y=2-x
}
y
}
And I'm trying to use this function as a parameter in my new function that should return the means of 1000 samples from this PDF, n times.
newpdf <- function(n, pdfx) {
array4 <- c()
for(i in 1:n) {
array4 = c(array4, mean(replicate(1000, pdfx)))
}
print(array4)
}
This doesn't work. It just returns 1 value n times, like this:
newpdf(10, pdf1())
[1] 0.07446415 0.07446415 0.07446415 0.07446415 0.07446415 0.07446415 0.07446415 0.07446415 0.07446415
[10] 0.07446415
But if I hard code in the PDF, like this:
newpdf <- function(n){
array4 <- c()
for(i in 1:n) {
array4 = c(array4, mean(replicate(1000, pdf1())))
}
print(array4)
}
It gives me exactly the values I want..
> newpdf(19)
[1] 0.4924323 0.5007244 0.4935517 0.5070427 0.4882152 0.5006345 0.5080305 0.4992261 0.5106020
[10] 0.5045957 0.5080413 0.5049816 0.5043062 0.4964958 0.4903163 0.5203326 0.5107542 0.5069920
[19] 0.4921472
So I'm not sure what's going on here. I have no idea why it's not able to understand the PDF as a parameter but it understands it when I hardcode it. Anyway, if somebody can help shed some light on this, that would be awesome!
You shouldn't use parenthesis after pdf1
when calling newpdf
, because you're passing the function name, not calling it.
Following the same logic, you should use them inside replicate()
.
pdf1 <- function() {
x = runif(1, min=0, max=2)
if(x <= 1) {
y = x
} else {
y=2-x
}
y
}
newpdf <- function(n, pdfx) {
array4 <- c()
for(i in 1:n) {
array4 = c(array4, mean(replicate(1000, pdfx())))
}
print(array4)
}
set.seed(1)
newpdf(19, pdf1)
[1] 0.5027618 0.4827648 0.4943929 0.4750925 0.4948409 0.5177700 0.4982195 0.5003837 0.5011541 0.4884556
[11] 0.5022072 0.4999359 0.4882833 0.4959163 0.5146288 0.4954670 0.5057518 0.5008227 0.5000727
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