[R-sig-finance] negative weights

[Spencer Graves]

	  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