Luc,
That sounds great - Thanks! I'll give that a try as well.
Cheers,
- Ole
On 01/31/2011 02:41 AM, luc.maison...@free.fr wrote:
- Ole Ersoyole.er...@gmail.com a écrit :
Hi,
Hi Ole,
I'm trying to fit a normal distribution to a curve (I'm assuming the
LM Optimizer is a good tool
Hi,
I'm trying to fit a normal distribution to a curve (I'm assuming the LM
Optimizer is a good tool for this). Is there a generic approach that lets me
construct a Jacobian or do I need specialized knowledge of the function in
order to do this?
TIA,
- Ole
Hi,
I'm trying to fit a normal distribution to a curve (I'm assuming the LM
Optimizer is a good tool for this). Is there a generic approach that lets me
construct a Jacobian or do I need specialized knowledge of the function in
order to do this?
TIA,
- Ole
Do you actually need an optimizer for this? What happened to computing the
mean and standard deviation and using those?
On Sun, Jan 30, 2011 at 5:08 PM, Ole Ersoy ole.er...@gmail.com wrote:
Hi,
I'm trying to fit a normal distribution to a curve (I'm assuming the LM
Optimizer is a good tool
It's a pretty unique case I agree. Long story, but I basically have the start
of what is a normal distribution (Sometimes I get to the top of the bell and
sometimes I get a 1/3 of the way). So I'd like to find the best fit mean and
variance for the set of points. I'm reading up on numerical
OK.
Are the data you have samples from this normal distribution?
I.e. are the samples you have from a truncated normal distribution where you
don't know the truncation point exactly?
Or do you actually have a truncated curve?
In the former case, I would define three parameters, mean, standard
On 01/30/2011 09:23 PM, Ted Dunning wrote:
I.e. are the samples you have from a truncated normal distribution where you
don't know the truncation point exactly?
Yes - and the points are always on the left side of the curve starting at zero
(So the mean is always greater than zer0)..
In
