It appears to me that rahul143 is a spammer who has automatated
extraction of old posts to Nabble as a way of delivering
advertisements. This is an exact copy of a posting to Nabble on
Mar 28, 2011; 2:33pm Worik StantonSullivan, Timmerman and White
1999: TA rules, and R
[Apologies if I have sent this multiple times. I have been struggling
with SMTP sewrvers and I have not seen my message appear on the list]
Friends
I am trying to save myself some tedious work.
I am processing a paper from "The Journal Of Finance * Vol. LIV,
No. 5
October 1999" by Sullivan, Timmerman and White. "Data-Snooping,
Technical Trading Rule Performance, and the Bootstrap"
This is not the only instance of his postings being identical to old
questions.
Here is another (and I suspect with diligent search all of them might
have been constructed the same way.)
:
Mar 28, 2011; 2:33pm Worik StantonSullivan, Timmerman and White
1999: TA rules, and R
[Apologies if I have sent this multiple times. I have been struggling
with SMTP sewrvers and I have not seen my message appear on the list]
Friends
I am trying to save myself some tedious work.
I am processing a paper from "The Journal Of Finance * Vol. LIV,
No. 5
October 1999" by Sullivan, Timmerman and White. "Data-Snooping,
Technical Trading Rule Performance, and the Bootstrap"
My advice is to divert his postings to your trash bin until his Nabble
account can be shut down.
--
David.
On Dec 2, 2012, at 7:33 AM, rahul143 wrote:
I'm trying to fit the Bass Diffusion Model using the nls function in
R but
I'm running into a strange problem. The model has either two or three
parameters, depending on how it's parameterized, p (coefficient of
innovation), q (coefficient of immitation), and sometimes m (maximum
market
share). Regardless of how I parameterize the model I get an error
saying
that the step factor has decreased below it's minimum. I have tried
re-setting the minimum in nls.controls but that doesn't seem to fix
the
problem. Likewise, I have run through a variety of start values in
the past
few days, all to no avail. Looking at the trace output it appears
that R
believes I always have one more parameter than I actually have (i.e.
when
the model is parameterized with p and q R seems to be seeing three
parameters, when m is also included R seems to be seeing four). My
experience with nls is limited, can someone explain to me why it's
doing
this? I've included the data set I'm working with (published in
Michalakelis
et al. 2008) and some example code.
## Assign relevant variables
adoption <-
c
(167000,273000,531000,938000,2056452,3894103,5932090,7963742,9314687,10469060,11393302,11976340
)
time <- seq(from = 1,to = 12, by = 1)
## Models
Bass.Model <- adoption ~ ((p + q)^2/p) * (exp(-(p + q) * time)/((q /
p) *
exp(-(p + q) * time) + 1)^2)
## Starting Parameters
Bass.Params <- list(p = 0.1, q = 0.1)
## Model fitting
-----
TO GET MORE DETAILS CLICK HERE
--
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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David Winsemius, MD
Alameda, CA, USA
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
