me this expression solution? I know there is uniroot, but here I
> want the "expression" not the value, because I do not have values for y and
> z.
I suggest the use of maxima rather than R. The two complement each
other very nicely: http://maxima.sf.net
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Daniel Lakeland
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an transforming from the standardized normal by hand.
qnorm(c(.025,.975),mean=mean(x100),sd=sd(x100)/sqrt(length(x100)))
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case we think of a particular
soil and weather and soforth causing a deviation from the trend, and
we think of that particular soil and weather also causing a deviation
from the between species trend in the last model.
As I say, I'm not an expert in this field, so I would be very glad if
someone
g(best.x,y)}
and use optim to optimize this new function varying only y.
Hope this helps.
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(19, mean=20,
> sd=10/sqrt(16))
> [1] 0.3108435
You have calculated the probability that your sample estimate of the
mean will be between 19 and 21, in your previous post you asked for 10
to 21, but I am guessing it was simply a typo. In any case, it looks
like you are on the right track.
-
rm can be used like your table of area under the normal curve. To
account for size of sample you have to scale the variance
appropriately according to the theory you have learned in your course.
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of the axis.
I think what he wants is the number of times that the current sample
is different from the previous sample. (ie. imagine heads = 1 and
tails = -1 how many times does the sequence change sign?)
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ce... These things almost always benefit from trying
various starting points, and from doing some analysis to determine a
good range of starting points.
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lation with factor
level 2. Compute the difference in averages. This is a single sample
of the "difference of averages". Do this procedure several thousand
times. You will have a bootstrap distribution of the difference in
averages.
Am I missing some other issue?
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Daniel Lakeland
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one can clarify what (if any) the differences are.
Thanks,
Dan
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PLEASE do read the posting gui
tried. Use "fitdistr" from the MASS package.
library(MASS)
fitdistr(mysample,"gamma") # parameters for your starting point
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On Wed, 2007-10-10 at 10:13 -0400, Tom Sgouros wrote:
> Hello all:
>
> I'm sure this is a trivial request, but I'm still a beginner at this,
> and haven't been able to find it. I need to create simulated data based
> on some empirical distributions of a single variable. I've found R
> functions
e). Perhaps you have a counter-example?
>
> Hadley
It can be useful to see multiple timeseries on the same x (time) scale
but with different y scales for each to see if there are time-lag
correlations between different quantities
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ct R to save my changes when I close the editing
> session ?
write.table
write.csv
or my favorite way of keeping data well organized is RSqlite or sqldf
(related)
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nterpolates
and returns 1.518
2) If you need an element of the data set, you could simply do
something like
(sort(x))[round(NROW(x) * p)]
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