Tal
Let me express some concern about using words like "true" or "real"
in relation to random number generation - for exactly the same reasons
as mentioned here:
http://xianblog.wordpress.com/2010/09/07/truly-random/
Device random number generators (whether provided via web-services or not)
should be regarded with as much skepticism as algorithmic generators, and
they typically don't have a set.seed() function for reproducibility -- you
would have to store the entire sequence.
- Niels
On 22/04/11 04.28, Tal Galili wrote:
BTW, Ken Kleinman recently wrote a post on how to get a "real" random
numbers (into R) from a web-service:
http://www.r-bloggers.com/example-8-35-grab-true-not-pseudo-random-numbers-passing-api-urls-to-functions-or-macros/
<http://www.r-bloggers.com/example-8-35-grab-true-not-pseudo-random-numbers-passing-api-urls-to-functions-or-macros/>
Cheers,
Tal
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On Fri, Apr 22, 2011 at 6:47 AM, Joshua Wiley<jwiley.ps...@gmail.com>wrote:
On Thu, Apr 21, 2011 at 8:34 PM, Penny Bilton<pennybil...@xnet.co.nz>
wrote:
Hi Josh,
Thanks for your reply.
The problem is have is in trying to retain the proportions of 2 groups in
my
data while sampling into training and test sets. I find that different
arguments for set.seed give very different proportions of my 2 groups in
the training and test sets.
Sure, just because numbers are random does not guarantee that equal
numbers from both groups will be sampled. Perhaps you are looking for
some sort of constrained random sampling like sampling x from group 1
and x from group 2? If so, try calling sample() separately on each
group (for help applying the same function to different groups, take a
look at ?by or ?tapply for example).
Josh
PS cced back to list
Penny.
On 22/04/2011 3:27 p.m., Joshua Wiley wrote:
Hi,
On Thu, Apr 21, 2011 at 8:18 PM, Penny Bilton<pennybil...@xnet.co.nz>
wrote:
I am using /set.seed()/ before the /sample/ function.
How does the length of the argument of /set.seed()/ and order of the
digits affect how the sampling is carried out?
You can use set.seed() to specify a particular seed so that while
pseudo-random numbers are sampled, you can repeat it. For example:
set.seed(10)
rnorm(10)
set.seed(10)
rnorm(10)
Specifically, I have used set.seed(123456789). Will this configuration
give me a genuinely random sampling??
You will never get truly random sampling from a computer algorithm,
but it is darn close and more than adequate in the majority of cases.
123456789 is just a length 1 vector containing the number 123456789,
not 9 separate numbers.
Google will be able to give you a lot of information on pseudo-random
number algorithms as well as the concept of "seeds". Also see
?set.seed
Cheers,
Josh
Thank you in anticipation.
Penny.
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--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/
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and provide commented, minimal, self-contained, reproducible code.
--
Niels Richard Hansen Web: www.math.ku.dk/~richard
Associate Professor Email: niels.r.han...@math.ku.dk
Department of Mathematical Sciences nielsrichardhan...@gmail.com
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