[R] Finding proportion of observations that are outliers from the left tail of the normal distribution

[Charles C. Berry]

On Mon, 19 Nov 2007, Thomas Frööjd wrote:

> Hi fellow users
>
> I have a new R problem i am hoping to get some pointers on. I have a
> dataset that is approximately normally distributed but with a fat left
> tail. I am interested in a good measurement on how much fatter the
> left tail is than can be expected from a normal distribution. One
> thing I'll  tried was fitting a two component mixture model with the
> Rmix package but i am also interested in other ideas. Now to my
> question.


Look at the qvalue package.

More generally, methods for estimating false discovery rates usually rely 
on an estimate of the fraction you describe (but typically consider 
both tails). I would guess that there are several packages on CRAN or in 
the Bioconductor suite that address this.

>
> I would like to calculate how many observations are "outside" the
> normal distribution on the left side. I want to do this by fitting a
> normal distributions and then use the proportion of observations not
> inside the bell curve on the left side as a statistic. Since I am
> relatively new to R I dont have very much success so far and would
> love any pointers or code examples. Bonus points are given for ideas
> on how to estimate standard errors.

If these are independent observations, try the boot package.


HTH,

Chuck


>
> Happy for any help.
>
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Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901