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var model:
### factors:
#### usa:
* real gdp - (GDP/CPI)
* inflation ln(CPI)
* exchange rate - ln(esch )
* short rate ln(1+R/100)
* long rate ln(1+R/100)
* stock rate (Index/CPI)?
…
msz13 updated
17 hours ago
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The pysteps.timeseries.autoregression module implements only a very basic version of the AR(p) model. More advanced time series models and parameter estimation methods could be implemented. For instan…
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The `statespace` component already has an excellent module for fitting Markov switching models; however, only univariate models are supported. Is there a way to extend it so as to support multivariate…
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I've just started looking into Tortoise. Impressive body of work.
Just by reading the wip paper, it's clear to me there is soo much under the hood to tweak and play with.
As I'd prefer to cont…
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My apologize for my selfish request. Your package really helps a lot to train various machine learning algorithms for time series based on caret library. May I request you an issue for a multivariate …
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Hi Dr. Nicholson,
I'm trying to understand the vector of parameters of the `gran()` argument in the `constructModel` function.
Your BigVAR guide states, "The first option controls the depth of the…
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Sequence Learning is a type of machine learning where information is gleaned from the order in which samples are presented to the learning algorithm. Sequence prediction is a type of inference that pr…
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Are there any plans or existing prototypes for extending the TFP STS API to handle multivariate observations?
I must admit to being somewhat new to STS, but I don't see any obvious theoretical limi…
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vector_ar.utils.varsim has `initvalues` option but those are not used.
`varsim(coefs, intercept, sig_u, steps=100, initvalues=None, seed=None)`
VARResults uses varsim in irf_errband_mc and irf_res…
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Hello Nick,
Thanks again for keeping your package updated and relevant.
I have a doubt regarding if your package considers the case of getting a forecast on one time series but related to many o…