On 21/03/2015 14:27, Johannes Radinger wrote:
Thanks for the fast response. The fitdistr() function works well for the
predefined density functions. However, what is the recommended approach
to optimize/fit a density function described by two superimposed normal
distributions? In my case it is N1(mean=0,sd1)*p+N2(mean=0,sd2)*(1-p).
With fitdistr one can only choose among the 15 distributions. Probably
That is simply not true. The help says
densfun: Either a character string or a function returning a density
evaluated at its first argument.
and the second alternative is used in the examples.
this needs an approach using optim()? However I am so far unfamiliar
with these packages. So any suggestion ist welcome. :)
There are examples of that in MASS (the book), chapter 16.
/Johannes
On Sat, Mar 21, 2015 at 2:16 PM, Prof Brian Ripley
<rip...@stats.ox.ac.uk <mailto:rip...@stats.ox.ac.uk>> wrote:
One way using the standard R distribution:
library(MASS)
?fitdistr
No optimization is needed to fit a normal distribution, though.
On 21/03/2015 13:05, Johannes Radinger wrote:
Hi,
I am looking for a way to fit data (vector of values) to a
density function
using an optimization (ordinary least squares or maximum
likelihood fit).
For example if I have a vector of 100 values generated with rnorm:
rnorm(n=100,mean=500,sd=50)
How can I fit these data to a Gaussian density function to
extract the mean
and sd value of the underlying normal distribution. So the
result should
roughly meet the parameters of the normal distribution used to
generate the
data. The results will ideally be closer the true parameters the
more data
(n) are used to optimize the density function.
That's a concept called 'consistency' from the statistical theory of
estimation. If you skipped that course, time to read up (but it is
off-topic here).
--
Brian D. Ripley, rip...@stats.ox.ac.uk <mailto:rip...@stats.ox.ac.uk>
Emeritus Professor of Applied Statistics, University of Oxford
1 South Parks Road, Oxford OX1 3TG, UK
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Emeritus Professor of Applied Statistics, University of Oxford
1 South Parks Road, Oxford OX1 3TG, UK
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