As a simple example, if I have y0 and a white noise series e,
what is the best way to produces a series y such that y[t] = 0.9*y[t-1] + e[t]
for t=1,2,...?
1. How can I best simulate an autoregressive process using NumPy?
2. With SciPy, it looks like I could do this as
e[0] = y0
On Fri, Oct 14, 2011 at 10:24 AM, Alan G Isaac alan.is...@gmail.com wrote:
As a simple example, if I have y0 and a white noise series e,
what is the best way to produces a series y such that y[t] = 0.9*y[t-1] + e[t]
for t=1,2,...?
1. How can I best simulate an autoregressive process using
Le vendredi 14 octobre 2011 à 10:49 -0400, josef.p...@gmail.com a
écrit :
On Fri, Oct 14, 2011 at 10:24 AM, Alan G Isaac alan.is...@gmail.com wrote:
As a simple example, if I have y0 and a white noise series e,
what is the best way to produces a series y such that y[t] = 0.9*y[t-1] +
e[t]
On Fri, Oct 14, 2011 at 11:56 AM, Fabrice Silva si...@lma.cnrs-mrs.fr wrote:
Le vendredi 14 octobre 2011 à 10:49 -0400, josef.p...@gmail.com a
écrit :
On Fri, Oct 14, 2011 at 10:24 AM, Alan G Isaac alan.is...@gmail.com wrote:
As a simple example, if I have y0 and a white noise series e,
On Fri, Oct 14, 2011 at 12:49 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 10/14/2011 12:21 PM, josef.p...@gmail.com wrote:
One other way to simulate the AR is to get the (truncated)
MA-representation, and then convolve can be used
Assuming stationarity ...
maybe ?
If it's integrated,
Assuming stationarity ...
On 10/14/2011 1:22 PM, josef.p...@gmail.com wrote:
maybe ?
I just meant that the MA approximation is
not reliable for a non-stationary AR.
E.g., http://www.jstor.org/stable/2348631
Cheers,
Alan
___
NumPy-Discussion mailing
On Fri, Oct 14, 2011 at 1:26 PM, Alan G Isaac alan.is...@gmail.com wrote:
Assuming stationarity ...
On 10/14/2011 1:22 PM, josef.p...@gmail.com wrote:
maybe ?
I just meant that the MA approximation is
not reliable for a non-stationary AR.
E.g., http://www.jstor.org/stable/2348631
section
On 10/14/2011 1:42 PM, josef.p...@gmail.com wrote:
If I remember correctly, signal.lfilter doesn't require stationarity,
but handling of the starting values is a bit difficult.
Hmm. Yes.
AR(1) is trivial, but how do you handle higher orders?
Thanks,
Alan
On Fri, Oct 14, 2011 at 2:18 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 10/14/2011 1:42 PM, josef.p...@gmail.com wrote:
If I remember correctly, signal.lfilter doesn't require stationarity,
but handling of the starting values is a bit difficult.
Hmm. Yes.
AR(1) is trivial, but how do
On Fri, Oct 14, 2011 at 2:18 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 10/14/2011 1:42 PM, josef.p...@gmail.com wrote:
If I remember correctly, signal.lfilter doesn't require stationarity,
but handling of the starting values is a bit difficult.
Hmm. Yes.
AR(1) is trivial, but how
On Fri, Oct 14, 2011 at 2:39 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Fri, Oct 14, 2011 at 2:18 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 10/14/2011 1:42 PM, josef.p...@gmail.com wrote:
If I remember correctly, signal.lfilter doesn't require stationarity,
but handling of the
On Fri, Oct 14, 2011 at 2:29 PM, josef.p...@gmail.com wrote:
On Fri, Oct 14, 2011 at 2:18 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 10/14/2011 1:42 PM, josef.p...@gmail.com wrote:
If I remember correctly, signal.lfilter doesn't require stationarity,
but handling of the starting values
On Fri, Oct 14, 2011 at 2:59 PM, josef.p...@gmail.com wrote:
On Fri, Oct 14, 2011 at 2:29 PM, josef.p...@gmail.com wrote:
On Fri, Oct 14, 2011 at 2:18 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 10/14/2011 1:42 PM, josef.p...@gmail.com wrote:
If I remember correctly, signal.lfilter
13 matches
Mail list logo
