R help - Feb 2013 - Fitting this data with a gaussian would be great

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.


Thanks in advance,
Samantha

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Samantha Warnes <warnes <at> wisc.edu> writes:
> 
> 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'm sorry, but as stated the question doesn't make much sense.
  You haven't stated your nonlinear model at all, and you haven't
said anything about any predictor variables.
  
  If you want fit a *constant* normal model you can

1. Compute the mean and standard deviation of the data (which
are the parameters of the model): mean(small), sd(small)

2. use an intercept-only model with lm(small~1) or glm(small~1)
(although the latter is definitely overkill)

3. You *can* use a nonlinear fitting method to estimate an
intercept-only model

nls(small~a,start=list(a=564000))

but it doesn't really mean much.

  Ben Bolker

Hello,

Why do you think your data is gaussian? For what it's worth,

qqnorm(small)  # doesn't look
qqline(small)  # gaussian

Hope this helps,

Rui Barradas

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.
>
>
> Thanks in advance,
> Samantha
>
> 	[[alternative HTML version deleted]]
>
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