[R-sig-finance] negative weights
Spencer Graves
spencer.graves at pdf.com
Fri May 5 16:57:43 CEST 2006
Weights in 'nls' and in forecasting are two very different things.
Weights in functions like 'nls', 'lm', 'lme', and often also 'optim' are
typically justified from a maximum likelihood argument. In that case,
the weights are (exactly or metaphorically, depending on context)
inversely proportional to the variances of the observations. Negative
weights in that context implies imaginary standard deviations; I'll let
you extrapolate from there.
Weights in forecasting, however, commonly occur when modeling, for
example, the output of a reactor: If the reactor delivers less than its
standard output on one cycle, it will often do the opposite on the next.
This is common with straight "moving average" models in the standard
time series literature, e.g., the famous Box and Jenkins (or Box,
Jenkins and Reinsel now) book "Time Series Analysis, Forecasting and
Control". Any good book on "arima" / "Box Jenkins" modeling should
discuss this. You can get started on this with the time series chapter
in the Venables and Ripley book, "Modern Applied Statistics with S".
hope this helps,
spencer graves
BBands wrote:
> On 4/28/06, Dirk Eddelbuettel <edd at debian.org> wrote:
>> So negative weights don't really fit that framework. That said, from a purely
>> numerical as opposed to statistical point of view you can probably minimize a
>> suitable expression with nls() or optim(). But you'd be 'on your own out
>> there'.
>
> Hi Dirk,
>
> I was looking for an all-in sort of solution, but preprocessing the
> data will get me where I need to go, so no traipsing around in the
> 'out there' for me. Perhaps I don't have the necessary statistical
> sophistication, but negative weights for linear models seem like a
> perfectly reasonable solution to the problem of different forecasting
> abilities at different horizons.
>
> jab
> --
> John Bollinger, CFA, CMT
> www.BollingerBands.com
>
> If you advance far enough, you arrive at the beginning.
>
> _______________________________________________
> R-sig-finance at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
More information about the R-sig-finance
mailing list