I'm studying R in my free time. I want to build a vector where each
element is equal to the element before it in the sequence plus some
random tweak.
In python, I would write:
vec = [100] * 50 # make a 50-element list with each element set to 100
from random import randint
for i, v in enumerate(vec):
if i is not 0: # if we're not on the first element
vec[i] = vec[i-1] + randint(-2, 2)
I suspect R has some fancier way of doing this. How to?
TIA
--
A better way of running series of SAS programs:
http://overlook.homelinux.net/wilsonwiki/SasAndMakefiles
Matthew Wilson <matt <at> overlook.homelinux.net> writes:> > I'm studying R in my free time. I want to build a vector where each > element is equal to the element before it in the sequence plus some > random tweak. >You will probably get many answers to this, but I think vec <- 100+c(0,cumsum(runif(49,-2,2))) works. Ben Bolker
On 8/3/2006 9:17 PM, Matthew Wilson wrote:> I'm studying R in my free time. I want to build a vector where each > element is equal to the element before it in the sequence plus some > random tweak. > > In python, I would write: > > vec = [100] * 50 # make a 50-element list with each element set to 100 > from random import randint > for i, v in enumerate(vec): > if i is not 0: # if we're not on the first element > vec[i] = vec[i-1] + randint(-2, 2) > > I suspect R has some fancier way of doing this. How to?Assuming randint(-2, 2) gives a value uniform on (-2, 2) a quick way to do what you want is vec <- 100 + c(0, cumsum(runif(49, -2, 2))) Duncan Murdoch
On 4 August 2006 at 01:17, Matthew Wilson wrote: | I'm studying R in my free time. I want to build a vector where each | element is equal to the element before it in the sequence plus some | random tweak. | | In python, I would write: | | vec = [100] * 50 # make a 50-element list with each element set to 100 | from random import randint | for i, v in enumerate(vec): | if i is not 0: # if we're not on the first element | vec[i] = vec[i-1] + randint(-2, 2) | | I suspect R has some fancier way of doing this. How to? Yup, cumsum() is your friend. You only need the first scalar of 100, vectorisation does the rest. Try> set.seed(12345) > Z <- 100 + cumsum(runif(50,-2,2)) > summary(Z)Min. 1st Qu. Median Mean 3rd Qu. Max. 98.54 100.80 102.30 102.10 103.40 105.70> plot(Z, type='l')Lastly, I think N(0, some_sd) is more customary that U(-2,2) but that is easy to change. Cheers, Dik -- Hell, there are no rules here - we're trying to accomplish something. -- Thomas A. Edison