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**Is your feature request related to a problem? Please describe.**
In some cases where models are very slow, you may wish to refresh a model with new data without refitting its' parameters. I thought…
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### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : Time Series Model on Counter Strike Market Sale Dataset
:red_circle: **Aim** : To develop a time series…
arpy8 updated
2 months ago
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I know my (p,d,q)(P,D,Q)_M (seven) coefficients, where should I put them? This library has only 6 coefficients as far as I could see.
This library has a nice sample code in README: https://github.c…
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### Is your feature request related to a problem? Please describe.
It would be nice to directly support simulating from a fitted ARIMA model, e.g. to have a `simulate` method to call that would deleg…
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I'm trying to use the code.
This section: from statsmodels.tsa.seasonal import seasonal_decompose
decomposition = seasonal_decompose(df_sample['SP500'], model='additive', freq=30)
plt.rcParams…
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Hi, do you have any solution to reduce the time processing when running the R function from VBA? I found out that it take more time when process Application.Run.
VBA script:
For i = 1 to 4
…
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Hello ,
I am trying to use Arima for some forecasting project. I see that the Arima in spark has following issues:
1] Input Series x = c(1.0,1.0,1.0,1.0)
Spark output : Infinite loop. It goes into i…
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_filing bug to follow up on known issue in Python unit tests_
In `test_ARIMA.py`, the `test_remodel_sample_data` unit test case fails with the following exception:
```
org.apache.commons.math3.excep…
pegli updated
8 years ago
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Would be massively useful to have a Seasoned ARIMA model for the time series analysis.
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Current arima model is a non-seasonal one. In our use cases we need to handle seasonal data. Hope to have a seasonal arima model for it.