> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of Wallace, John
> Sent: Friday, August 05, 2005 7:03 PM
> To: [email protected]
> Subject: st: predictnl and nonlinear regression
>
> Dear listmembers:
> I'm working my way through learning how to use regressions other than OLS
> within stata. One model I frequently use in Excel is the exponential fit.
> I believe the following is the way to specify that model within Stata's nl
> function:
> nl(y = {beta}*exp({alpha}*x)
> I have used the predict function following this estimation to generate a
> fit and graphed the results, which look like the chart I was expecting to
> see. I then looked for a way to generate confidence intervals for the
> fit, and have run aground. It looks like the predictnl function would do
> what I want, but I can't get it to work. Here's what I've tried:
> (after first -drop-ing the fit variable I made with -predict-)
>
> . predictnl fit = predict(fit), ci(ub lb)
> Result: fit not allowed \\\ predict(fit) invalid
> . predictnl fit = nl (y = {beta}*exp({alpha}*x)), ci(ub lb)
> Result: Unknown function nl()
> . predictnl fit = y = {beta}*exp({alpha}*x), ci(ub lb)
> Result: =exp not allowed
You don't need the y term in the -predictnl- statement.
For example:
. sysuse auto,clear
(1978 Automobile Data)
. qui nl (price = {beta}*exp({alpha}*mpg))
. predictnl fit = _b[beta]*exp(_b[alpha]*mpg), ci(lb ub)
note: Confidence intervals calculated using t(72) critical values.
> Also, is it possible to use the stored estimation command interactively to
> solve for a specific x?
> e.g.: . predicti(0.5)
> which returns some value y according to the model?
>
How about using -nlcom-. For example, if price = 1000:
. nlcom (ln(1000/_b[beta]))/_b[alpha]
_nl_1: (ln(1000/_b[beta]))/_b[alpha]
----------------------------------------------------------------------------
--
price | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
_nl_1 | 52.22725 6.330777 8.25 0.000 39.60708
64.84742
----------------------------------------------------------------------------
--
Hope this helps,
Scott
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