pymc3 for ARIMAX model
I have one observed series as the sum of three latent random series
where F and G are explanatory variables. F, G, and O are observed. Is it possible to model this under Bayesian framework (assuming a, b, beta having normal prior) by pymc3?
I know Z can be defined as pymc3.distributions.timeseries.GaussianRandomWalk, but how can I define X and Y?
python pymc3
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
add a comment |
I have one observed series as the sum of three latent random series
where F and G are explanatory variables. F, G, and O are observed. Is it possible to model this under Bayesian framework (assuming a, b, beta having normal prior) by pymc3?
I know Z can be defined as pymc3.distributions.timeseries.GaussianRandomWalk, but how can I define X and Y?
python pymc3
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
add a comment |
I have one observed series as the sum of three latent random series
where F and G are explanatory variables. F, G, and O are observed. Is it possible to model this under Bayesian framework (assuming a, b, beta having normal prior) by pymc3?
I know Z can be defined as pymc3.distributions.timeseries.GaussianRandomWalk, but how can I define X and Y?
python pymc3
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
I have one observed series as the sum of three latent random series
where F and G are explanatory variables. F, G, and O are observed. Is it possible to model this under Bayesian framework (assuming a, b, beta having normal prior) by pymc3?
I know Z can be defined as pymc3.distributions.timeseries.GaussianRandomWalk, but how can I define X and Y?
python pymc3
python pymc3
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
asked Nov 19 '18 at 22:26
jf328jf328
1,99032040
1,99032040
add a comment |
add a comment |
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