Hi,
Define Y = X if X<=T
= 0 otherwise
For your problem, T=150 (threshold) and X is exponential random variable
with mean, MU.
So, first generate X and compare with T and assign a value to Y as
specified in the above rule.
Alternatively, find the CDF (distribution funct
Linda wrote in message <[EMAIL PROTECTED]>...
>I want to generate a series of random variables, X with exponential
>PDF with a given mean,MU value. However, I only want X to be in some
>specified lower and upper limit?? Say between 0 -> 150 i.e. rejected
>anything outside this range Does anyone ha
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In article <[EMAIL PROTECTED]>,
[EMAIL PROTECTED] (Linda) wrote:
>I want to generate a series of random variables, X with exponential
>PDF with a given mean,MU value. However, I only want X to be in some
>specified lower and upper limit?? Say between 0 -> 150 i.e. rejected
>anything outside this
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I want to generate a series of random variables, X with exponential
PDF with a given mean,MU value. However, I only want X to be in some
specified lower and upper limit?? Say between 0 -> 150 i.e. rejected
anything outside this range Does anyone have any ideas how should I do
that??
Regards,
Lind
George Marsaglia wrote in message
<0l7b8.42092$[EMAIL PROTECTED]>...
>
.. chunk deleted
>
>The Monty Python method is not quite as fast as as the Ziggurat.
>
>Some may think that Alan Miller's somewhat vague reference to
>a source for the ziggurat article suggests disdain. The source is
>Journ
Hi all:
I would appreciate your help in solving this question.
calculate the standard deviation of a sample where the mean and
standard deviation from the process are provided?
E.g. Process mean = 150; standard deviation = 20. What is the SD for
a sample of 25? The answer suggested is 4.0
TI
Art Kendall <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> I tend to be more concerned with the "apparent randomness" of the results than with
>the speed
of the algorithm.
>
> As a thought experiment, what is the cumulative time difference in a run using th
[ snip, previous problem]
>
> This is similar to a problem I have come across: the measurement of a
> serum value against exposure.
> My theory is that they are correlated. But the data says that they
> have an R^2 of 0.02 even though the p-value for the beta is p=1E-40
> (ie. zero).
>
> As y
and will you not, by this approach, wind up making a _lot_ of pairwise comparisions,
with all the implications that have recently been disucssed even here at edstat?
Messing with weakly formed data rarely strethens it. I love some transformations, but
take them for what they are.
Jay
Thomas
On 14 Feb 2002 17:14:24 -0800, [EMAIL PROTECTED] (Thomas Souers)
wrote:
TS>
> I have another question regarding one-way ANOVA. I have noticed
> that in some books, nothing is said about what you can do when the
> factor level variances are unequal. In Neter's big book,
> transformations are reco
On Thu, 14 Feb 2002 23:48:02 +0100, "Matthias" <[EMAIL PROTECTED]>
wrote:
> Hello,
>
> would be nice if someone can give me some advice with regard to the
> following problem:
>
> I would like to compare the means of two independent numerical sets of data
> whether they are significantly differ
Back in 1970, Glass and Stanley in their excellent Statistical Methods in
Education and Psychology book, Prentice-Hall ... had an excellent chapter
on several of the more important distributions used in statistical work
(normal, chi square, F, and t) and developed how each was derived from the
In SPSS output ignore the lines for equal variances, and use the lines for
unequal variances.
Matthias wrote:
> Hello,
>
> would be nice if someone can give me some advice with regard to the
> following problem:
>
> I would like to compare the means of two independent numerical sets of data
> w
I tend to be more concerned with the "apparent randomness" of the results than with
the speed of the algorithm.
As a thought experiment, what is the cumulative time difference in a run using the
fastest vs the slowest algorithm? A
whole minute? A second? A fractional second?
Glen wrote:
> "A
Excuse the bad grammar or typo noted below... It's been a "long
morning" already, and it's still not 9 am...
:)
Bill
On Fri, 15 Feb 2002, William B. Ware wrote:
> What are your samples sizes? If there are equal or nearly so, the t-test
*they*
> is robust wit
Marsaglia's ziggurat and MCW1019 generators are
available in the R package SuppDists. The gcc
compiler was used.
George Marsaglia wrote:
>
> Glen <[EMAIL PROTECTED]> wrote in message
> [EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> > "Alan Miller" <[EMAIL PROTECTED]> wrote in message
> news:
What are your samples sizes? If there are equal or nearly so, the t-test
is robust with regard to unequal variances.
On the other hand, you could just read the part of the output that reports
results for "equal variances not assumed." You might also consider using
a nonparametric procedure such
Glen <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> "Alan Miller" <[EMAIL PROTECTED]> wrote in message
news:...
> > The fastest way to generate random normals and exponentials is to use George
> > Marsaglia's ziggurat algorithm.
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