You may find it easier to use the logspline density fits (logspline
package) rather than the kernel density estimators for this.
On Mon, Oct 1, 2012 at 7:46 AM, Eugene Kanshin wrote:
> Hello,
> I have a data x with normal (or very close to normal) distribution, I can
> plot a density distribution
On Oct 1, 2012, at 6:46 AM, Eugene Kanshin wrote:
> Hello,
> I have a data x with normal (or very close to normal) distribution, I can
> plot a density distribution with density(x,...). My question is is there
> any way to calculate an area under this distribution (=probability) for
> particular
Forget density(). Smooth the ecdf instead.
?lowess
?smooth.spline
?monotone.smooth (in package fda, for monotone smoothing, which may be
preferable)
?locfit (in package locfit)
... and many many others
-- Bert
On Mon, Oct 1, 2012 at 6:46 AM, Eugene Kanshin wrote:
> Hello,
> I have a data x wit
Hello,
I have a data x with normal (or very close to normal) distribution, I can
plot a density distribution with density(x,...). My question is is there
any way to calculate an area under this distribution (=probability) for
particular range of x values, let's say for x from 0 to 2? I was not able
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