I think you are confusing the idea of a sample with the source of a
binomial random variable. The binomial model applies when some action is
repeated a specified number of times, n; when we are interested in the
occurrence or not of some outcome; when the probability of that outcome
is the same
On Tue, 10 Apr 2001, Gary Carson wrote:
It's the proportion of success (x/n) which has approxiatmenly a normal
distribution for large n, not the number of success (x).
Both are approximately normal.
(If the r.v. W = (x/n) is (approximately) normally distributed, then
the r.v. V = x = n*W
I have a question that probably applies to ARIMA forecasting in general,
but the specific piece of econometrics software I'm using is EViews.
When I use an ARIMA(1,1,0) model to model ~150 pieces of stock market
data and then use the EViews software to forecast the next 100 values,
Every
[EMAIL PROTECTED] (James Ankeny) writes:
[snip]
Typically, a binomial rv is not thought of as a statistic, at least in these
books, but this is the only way that the approximation makes sense to me.
Actually, the binomial rv is the sufficient statistic for the data,
which are represented as
[EMAIL PROTECTED] (Jason Owen) writes:
[EMAIL PROTECTED] (James Ankeny) writes:
[snip]
Typically, a binomial rv is not thought of as a statistic, at least in these
books, but this is the only way that the approximation makes sense to me.
Actually, the binomial rv is the sufficient statistic
If I remember correctly two vectors are independent if their cross product
is zero. Check a vector analysis book for verification of this.
WDA
end
"Peter J. Wahle" [EMAIL PROTECTED] wrote in message
N%FA6.403$[EMAIL PROTECTED]">news:N%FA6.403$[EMAIL PROTECTED]...
What can I tell about the
Without any relation to the type of your data (stock market) : ARMA is a
way to model a data with no long-range dependence. Correlation among
observations dies out really fast ( at exponential rate ), so when you
trying to forecast out of sample, you realise very soon that the past data
contains
You may be interested in an applet I have on my website demonstrating the
normal approximation to the binomial.
http://www.ruf.rice.edu/~lane/stat_sim/normal_approx/index.html
--David
From: [EMAIL PROTECTED] (James Ankeny)
Organization: None
Newsgroups: sci.stat.edu
Date: 9 Apr 2001
The cross product is another vector.
Two vectors are orthogonal if their dot product is zero.
This is not what I'm looking for.
I have two sets of 2-D vectors that I need to
determine their correlation or dependence.
If I remember correctly two vectors are independent if their cross product
