Hi Dimitri, Ted,
thanks for both taking the time to provide such detailed and
interesting answers. I now need to digest all this.
>From what I already understand, I think that Gilles' suggestion, which
we finally settled for was probably the best one!
Best regards,
Sébastien
-
This sort of problem can often be approached from a Bayesian point of view
with a result that is a bit more intuitive.
The basic idea for this is that the data are measurements that come from
some process that is parameterized. These parameters are sampled from some
very non-specific distribution
Sebastien,
Hi Dimitri,
I'm obviously missing something in my litterature review. I did a new
MC simulation, with a much smaller number of observation points
(namely 3, to fit a straight line!!!). It turns out that the formula
you are advocating for is the best estimate of the standard deviation
Hi,
>
>>
>> Before closing the issue, I'd like to commit the "test" I've attached to
>> MATH-784. It's not really a "unit" test (as it doesn't "assert" anything
>> yet) but it shows the meaning of "sigma".
>> I've ended the class name with the string "TestValidation" so that it does
>> not run by d
Hi Gilles,
>
> Before closing the issue, I'd like to commit the "test" I've attached to
> MATH-784. It's not really a "unit" test (as it doesn't "assert" anything
> yet) but it shows the meaning of "sigma".
> I've ended the class name with the string "TestValidation" so that it does
> not run by d
> > [...]
> > For clarity's sake (design-wise), I propose to remove the
> > "guessParametersErrors" method, and add a "getSigma" (as syntactic sugar).
> >
> I'm OK with that. As a first step, we deprecate it, and stipulate in
> the javadoc that getSigma() should be used instead. We emphasize that
>
2012/5/4 Gilles Sadowski :
> Hello.
>
>> I'm obviously missing something in my litterature review. I did a new
>> MC simulation, with a much smaller number of observation points
>> (namely 3, to fit a straight line!!!). It turns out that the formula
>> you are advocating for is the best estimate o
Hello.
> I'm obviously missing something in my litterature review. I did a new
> MC simulation, with a much smaller number of observation points
> (namely 3, to fit a straight line!!!). It turns out that the formula
> you are advocating for is the best estimate of the standard deviation
> of the
Hi Dimitri,
I'm obviously missing something in my litterature review. I did a new
MC simulation, with a much smaller number of observation points
(namely 3, to fit a straight line!!!). It turns out that the formula
you are advocating for is the best estimate of the standard deviation
of the parame
Hi Dimitri,
I think we agree on the two different concepts (sd of the parameters,
and confidence interval), and we also agree that the terminology in CM
should be precise.
For the moment, the formula for guessParametersErrors is
sqrt(chi^2 / dof * cov[i][i])
this is I believe the formula for the st
Hi,
Hi,
attached to MATH-784 (https://issues.apache.org/jira/browse/MATH-784)
is a Monte-Carlo simulation which might be used to explore this issue.
For the time being, it confirms that
* guessParametersErrors() indeed estimates the sd on the parameters,
* the sqrt of the diagonal coefficients o
Hi,
attached to MATH-784 (https://issues.apache.org/jira/browse/MATH-784)
is a Monte-Carlo simulation which might be used to explore this issue.
For the time being, it confirms that
* guessParametersErrors() indeed estimates the sd on the parameters,
* the sqrt of the diagonal coefficients of the c
BTW, I've just noticed the very poor subject of this thread. I'm sorry
for that, was too quick clicking the "send" button.
Sébastien
-
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Hi,
2012/5/3 Gilles Sadowski :
> Hello.
>
>> in this thread,
>> http://mail-archives.apache.org/mod_mbox/commons-dev/201204.mbox/%3C20120418122114.GB32074%40dusk.harfang.homelinux.org%3E
>> I suggested that we deprecate guessParametersErrors() and replace it
>> with getParametersStandardDeviation()
Hello.
> in this thread,
> http://mail-archives.apache.org/mod_mbox/commons-dev/201204.mbox/%3C20120418122114.GB32074%40dusk.harfang.homelinux.org%3E
> I suggested that we deprecate guessParametersErrors() and replace it
> with getParametersStandardDeviation(), since the implemented formula
> seem
Sebastien,
Hi,
in this thread,
http://mail-archives.apache.org/mod_mbox/commons-dev/201204.mbox/%3C20120418122114.GB32074%40dusk.harfang.homelinux.org%3E
I suggested that we deprecate guessParametersErrors() and replace it
with getParametersStandardDeviation(), since the implemented formula
seem
Le 14/11/2010 17:19, Luc Maisonobe a écrit :
> Hello,
>
> One large change that was done for version 2.1 was to add a way to
> compute the partial derivatives of an ODE final state with respect to
> both its initial state and problem parameters. This was done by creating
> a new ode.jacobians pack
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