RE: st: qnorm

[amir gahremanpour <gamirali@hotmail.com>]

Nick and Maarten,
 
 
Thank you all so much for your compelling answers and explanations. I am glad I decided to bring these questions about normality and qnorm to this website. I always learn alot here, I like to call it  "stata-free university" !
 
 
best regards
 
Amir


> From: n.j.cox@durham.ac.uk
> To: statalist@hsphsun2.harvard.edu
> Date: Mon, 5 Mar 2012 15:23:52 +0000
> Subject: RE: st: qnorm
> 
> The approach in Maarten's program is to generate a number of random samples and show the lot as replicates. 
> 
> Here as an alternative is some example code for individual 95% confidence intervals for each plotted point. -qplot- used at the end is from SJ. The code isn't smart about missing values, but it could easily be made smarter. I also guess the code could be shortened in the middle. 
> 
> sysuse auto, clear
> 
> mata 
> y = sort(st_data(., "mpg"), 1) 
> mean = mean(y)
> sd = sqrt(variance(y)) 
> n = rows(y) 
> 
> compare = J(n, 0, .)
> 
> for (j = 1; j <= 100; j++) { 
> compare = compare, sort(rnormal(n, 1, mean, sd), 1) 
> }
> 
> envelope = J(n, 2, .) 
> for (i = 1; i <= n; i++) { 
> x = sort(compare[i,]', 1) 
> envelope[i,] = ((x[2] + x[3])/2, (x[97] + x[98])/2) 
> } 
> 
> names = tokens("_lower _upper") 
> (void) st_addvar("float", names) 
> st_store(., names, envelope) 
> 
> end 
> 
> qplot mpg _lower _upper, ms(O i i) c(. J J) legend(off) ytitle("`: var label mpg'") 
> 
> Nick 
> n.j.cox@durham.ac.uk 
> 
> Maarten Buis
> 
> On Mon, Mar 5, 2012 at 10:03 AM, Nick Cox wrote:
> > 1. Simulate several samples from a distribution with the same mean and
> > standard deviation (or more generally an appropriate mean and standard
> > deviation) and use the resulting portfolio of plots in assessing what
> > kind of variability is to be expected.
> 
> An easy way to do so is to use the -margdistfit- package, which you
> can install by typing in Stata -ssc install margdistfit-. The default
> is actually to first sample the mean and the standard deviation from
> its sampling distribution and than sample a new variable with those
> sampled means and standard deviation. I suspect that this makes sense
> in most cases, though I also suspect that it won't matter much. If you
> want to do exactly what Nick proposes you can add the -noparsamp-
> option.
> 
> Here is an example of what such a graph would look like:
> 
> *-------- begin example -----------
> sysuse auto, clear
> reg mpg
> margdistfit, qq name(qq)
> margdistfit, pp name(pp)
> margdistfit, hangroot name(hangr)
> margdistfit, cumul name(cumul)
> *--------- end example ------------
> (For more on examples I sent to the Statalist see:
> http://www.maartenbuis.nl/example_faq )
> 
> Hope this helps,
> Maarten
> 
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
> 
> 
> http://www.maartenbuis.nl
> --------------------------
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
> 
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/ 		 	   		  
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/