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1. Data Collection
Gather historical data on:
Indian General Election dates and outcomes.
Historical stock market data (e.g., BSE Sensex and NSE Nifty).
Macroeconomic indicators (e.g., inflati…
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```python
from kats.models.theta import ThetaModel, ThetaParams
params = ThetaParams(m=7) # Weekly seasonality
m = ThetaModel(data_ts, params) # data_ts -> daily data points
m.fit()
```
gives t…
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We need to create an ARIMA model on the LOB data. We may choose to model a forecast on max bid, min ask.
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After chat with @felix, we will try to proceed on the build a script as follow :
1/ Input : token
2/ Get the daily steps data in a python dataframe (cols : DATE, STEPS, USER_TOKEN)
Bonus:
3/ S…
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Need to generate an SARIMA(p,d,q)x(P,D,Q)_s.
To go about this, we need to retain the theta vector list since if we include place holders (e.g. 0's), we will run into optimization issues.
Furthermor…
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# Tweet summary
When having seasonality more than 3 lags in data points, we should use SARIMAX as parameter d
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I'm currently doing some forecasting on daily data and I was wondering whether is there a problem whenever i add exogenous variables (like the day of the week or month of the year) provided as one-ho…
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Hello,
Thanks for your effort and sharing your code.
I am receiving the following error for the Holt-Winters method, using the Kaggle train data.
"TypeError: __new__() got an unexpected keywo…
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It would be useful to be able to specify the simulated innovations. Often I'm combining ARIMA models for some variables with different models for others and using a copula framework to simulated the …