download it?
Netlib has all the TOMS (= Transactions Of Mathematical Software)
algorithms. Look for '814'.
Regards,
Martin
S - Original Message -
S From: David Duffy [EMAIL PROTECTED]
S Date: Wednesday, July 13, 2005 9:46 am
S Subject: [R] exact values for p-values
)
algorithms. Look for '814'.
Regards,
Martin
S - Original Message -
S From: David Duffy [EMAIL PROTECTED]
S Date: Wednesday, July 13, 2005 9:46 am
S Subject: [R] exact values for p-values
This is obtained from F =39540 with df1 = 1, df2 = 7025.
Suppose am
This is obtained from F =39540 with df1 = 1, df2 = 7025.
Suppose am interested in exact value such as
If it were really necessary, you would have to move to multiple
precision. The gmp R package doesn't seem to yet cover this, but FMLIB
(TOMS814, DM Smith) is a multiple precision f90 library
Hi David, Since I am looking at very extreme values, it appears I will
need FMLIB. Is it an R lib? if so which version? How/where can I
download it?
Regards.
- Original Message -
From: David Duffy [EMAIL PROTECTED]
Date: Wednesday, July 13, 2005 9:46 am
Subject: [R] exact values
so my chi-square approximation was not very good:
pchisq(39540, 1, lower.tail=FALSE, log.p=TRUE)
[1] -19775.52
(pchisq(39540, 1, lower.tail=FALSE, log.p=TRUE)
+ /log(10))
[1] -8588.398
... roughly 1e-8588. With a few hours with Abramowitz and Stegun, I
suspect I could
, 2005 7:39 pm
Subject: Re: [R] exact values for p-values - more information.
I just checked:
pf(39540, 1, 7025, lower.tail=FALSE, log.p=TRUE)
[1] -Inf
This is not correct. With 7025 denominator degrees of
freedom, we
might use the chi-square approximation
If they have the same degrees of freedom, use the test statistic
and not
the p value for comparing them.
Z
I appretiate your input to this discussion. Do you know of a reference
to your statement above?
I had actually used the test-statistic which in my case is r-squared
to compare them.
On Tue, 12 Jul 2005, S.O. Nyangoma wrote:
If they have the same degrees of freedom, use the test statistic
and not
the p value for comparing them.
Z
I appretiate your input to this discussion. Do you know of a reference
to your statement above?
?? Any basic statistics book?
On Jul 11, 2005, at 11:47 AM, S.O. Nyangoma wrote:
Hi there,
If I do an lm, I get p-vlues as
p-value: 2.2e-16
Suppose am interested in exact value such as
p-value = 1.6e-16 (note = and not )
How do I go about it?
stephen
I think you're seeing a very small p-value after it has been
Hi there,
If I do an lm, I get p-vlues as
p-value: 2.2e-16
Suppose am interested in exact value such as
p-value = 1.6e-16 (note = and not )
How do I go about it?
stephen
__
R-help@stat.math.ethz.ch mailing list
Hi there,
If I do an lm, I get p-vlues as
p-value: 2.2e-16
This is obtained from F =39540 with df1 = 1, df2 = 7025.
Suppose am interested in exact value such as
p-value = 1.6e-16 (note = and not )
How do I go about it?
stephen
__
On Mon, 11 Jul 2005, S.O. Nyangoma wrote:
Hi there,
If I do an lm, I get p-vlues as
p-value: 2.2e-16
This is obtained from F =39540 with df1 = 1, df2 = 7025.
Suppose am interested in exact value such as
p-value = 1.6e-16 (note = and not )
How do I go about it?
You can always
I just checked:
pf(39540, 1, 7025, lower.tail=FALSE, log.p=TRUE)
[1] -Inf
This is not correct. With 7025 denominator degrees of freedom, we
might use the chi-square approximation to the F distribution:
pchisq(39540, 1, lower.tail=FALSE, log.p=TRUE)
[1]
Compare the following
t.test( 1:100, 101:200 )$p.value
t.test( 1:100, 101:200 )
In the latter, the print method truncates to 2.2e-16.
You can go as far as (depending on your machine)
.Machine$double.xmin
[1] 2.225074e-308
before it becomes indistinguishable from zero.
But there
an article using this method?
Regards. Stephen.
- Original Message -
From: Spencer Graves [EMAIL PROTECTED]
Date: Monday, July 11, 2005 7:39 pm
Subject: Re: [R] exact values for p-values - more information.
I just checked:
pf(39540, 1, 7025, lower.tail=FALSE, log.p=TRUE
: Monday, July 11, 2005 7:39 pm
Subject: Re: [R] exact values for p-values - more information.
I just checked:
pf(39540, 1, 7025, lower.tail=FALSE, log.p=TRUE)
[1] -Inf
This is not correct. With 7025 denominator degrees of
freedom, we
might use the chi-square approximation
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