# [R] Fitting this data with a gaussian would be great

David Winsemius dwinsemius at comcast.net
Sat Feb 23 20:29:35 CET 2013

```On Feb 23, 2013, at 11:09 AM, Rui Barradas wrote:

> Hello,
>
> Why do you think your data is gaussian? For what it's worth,
>
> qqnorm(small)  # doesn't look
> qqline(small)  # gaussian

It's a bit hard to say with such a small sample, isn't it? Here's a poor man's functional data analysis:

plot(density(small), lwd=3, col="red")
set.seed(123)
for(i in 1:25){ lines(density( rnorm(24, mean(small), sd(small) ) ), col=i ) }
for(i in 1:25){ lines(density( rnorm(24, mean(small), sd(small) ) ), col=i ) }
for(i in 1:25){ lines(density( rnorm(24, mean(small), sd(small) ) ), col=i ) }
for(i in 1:25){ lines(density( rnorm(24, mean(small), sd(small) ) ), col=i ) }

I agree that it does appear that the distribution might be reasonably said to be "outside" the "dominant envelope" of densities for samples of normals with the same mean and sd, but you do see a few in that are "as extreme" or more so on some functional eyeball distance metric than a perfect Normal density with the same mean and sd as the offered case.

>
> Hope this helps,
>
>
> Em 22-02-2013 23:27, Samantha Warnes escreveu:
>> Hello,I'm still working with this data set, and trying to fit it with a nonlinear model. Here is my data
>>> small <- c(507680,507670,508832,510184,511272,513380,515828,519160,525046,534046,547982,567124,590208,614506,637876,656846,669054,672976,668800,656070,637136,614342,590970,570752,554480,542882,535630,531276,528682,527682,527020,526834,526802,526860)
>>
>>
>> test <- glm(dnorm(x), data=small)
>> Error in formula.default(object, env = baseenv()) : invalid formula
>>
>>
>> I have tried a variety of options for the formula with the same effect. What I want to do with this data is simply fit it with a non linear model, most likely a gaussian.
>>
>>