Why are all coefficients of my seasonal ARIMA = 0 or NaN?

4 visualizaciones (últimos 30 días)
MC3105
MC3105 el 26 de Sept. de 2014
Comentada: Roger Wohlwend el 29 de Sept. de 2014
Hello everyone!
I created a seasonal ARIMA model with the following code:
% model = arima('Constant',0,'D',1,'Seasonality',24,'ARLags',3,'SARLags',3,'MALags',2,'SMALags',2);
[fit,VarCov,LogL,info] = estimate(model,Y);
Now matlab gives me the following output:
Parameter Value Error Statistic
----------- ----------- ------------ -----------
Constant 0 Fixed Fixed
AR{3} -0.0321142 0.00310401 -10.346
SAR{3} -0.0321142 0.00310401 -10.346
MA{2} -0.138189 0.00201315 -68.643
SMA{2} -0.138189 0.00201315 -68.643
Variance 0.921722 0.00357711 257.672
When I try to retrieve the coefficients of my polynomials with for example
% model.SAR
I only get zeros and NaN as coefficients. Does anyone know what the problem could be?
Thanks a lot!! I am very new to matlab, so help is greatly appreciated!!

Respuesta aceptada

Roger Wohlwend
Roger Wohlwend el 26 de Sept. de 2014
The variable model specifies the model but it does not contain any values for the coefficients (except the constant). That is why you only get zeros and NaNs. The estimated model is the variable fit . You have to retrieve the coeffiencts from that variable.
SAR = fit.SAR
  2 comentarios
MC3105
MC3105 el 26 de Sept. de 2014
Thank you so much for your answer!
When I retrieve my coefficients now, I only get a coefficient for the last polynomial. For example for
fit.SAR
i get the output
[0] [0] [-0.0321142]
meaning that I basically only have a SAR polynomial with one variable (the variable at lag 3).
Normally a seasonal ARIMA that is specified as (3,1,2)x(3,1,2) should have 3 AR and 3 SAR variables as well as 2 MA and 2 SMA variables (one variable for each lag), right?
Is there a different way to tell matlab what I want exactly?
Roger Wohlwend
Roger Wohlwend el 29 de Sept. de 2014
You have to include all lags in the specification, not just the highest one. With the following line of code Matlab will estimate the model you want:
model = arima('Constant', 0, 'D', 1, 'Seasonality', 24, 'ARLags', 1:3, 'SARLags', 1:3, 'MALags', 1:2, 'SMALags', 1:2);

Iniciar sesión para comentar.

Más respuestas (0)

Categorías

Más información sobre Conditional Mean Models en Help Center y File Exchange.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by