I have a problem with time series analysis. I have a dataset with 5 features. Following is the subset of my input dataset:
date,price,year,day,totaltx
1/1/2016 0:00,434.46,2016,1,126762
1/2/2016 0:00,433.59,2016,2,147449
1/3/2016 0:00,430.36,2016,3,148661
1/4/2016 0:00,433.49,2016,4,185279
1/5/2016 0:00,432.25,2016,5,178723
1/6/2016 0:00,429.46,2016,6,184207
My endogenous data is price column and exogenous data is totaltx price.
This is the code I am running and getting an error:
import statsmodels.api as sm
import pandas as pd
import numpy as np
from numpy.linalg import LinAlgError
def arima(filteredData, coinOutput, window, horizon, trainLength):
start_index = 0
end_index = 0
inputNumber = filteredData.shape[0]
predictions = np.array([], dtype=np.float32)
prices = np.array([], dtype=np.float32)
# sliding on time series data with 1 day step
while ((end_index) < inputNumber - 1):
end_index = start_index + trainLength
trainFeatures = filteredData[start_index:end_index]["totaltx"]
trainOutput = coinOutput[start_index:end_index]["price"]
arima = sm.tsa.statespace.SARIMAX(endog=trainOutput.values, exog=trainFeatures.values, order=(window, 0, 0))
arima_fit = arima.fit(disp=0)
testdata=filteredData[end_index:end_index+1]["totaltx"]
total_sample = end_index-start_index
predicted = arima_fit.predict(start=total_sample, end=total_sample, exog=np.array(testdata.values).reshape(-1,1))
price = coinOutput[end_index:end_index + 1]["price"].values
predictions = np.append(predictions, predicted)
prices = np.append(prices, price)
start_index = start_index + 1
return predictions, prices
def processCoins(bitcoinPrice, window, horizon):
output = bitcoinPrice[horizon:][["date", "day", "year", "price"]]
return output
trainLength=100;
for window in [3,5]:
for horizon in [1,2,5,7,10]:
bitcoinPrice = pd.read_csv("..\\prices.csv", sep=",")
coinOutput = processCoins(bitcoinPrice, window, horizon)
predictions, prices = arima(bitcoinPrice, coinOutput, window, horizon, trainLength)
In this code, I am using rolling window regression technique. I am training arima for start_index:end_index and predicting the test data with end_index:end_index+1
This the error that is thrown from my code:
Traceback (most recent call last):
File "C:/PycharmProjects/coinLogPrediction/src/arima.py", line 115, in <module>
predictions, prices = arima(filteredBitcoinPrice, coinOutput, window, horizon, trainLength, outputFile)
File "C:/PycharmProjects/coinLogPrediction/src/arima.py", line 64, in arima
arima_fit = arima.fit(disp=0)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\tsa\statespace\mlemodel.py", line 469, in fit
skip_hessian=True, **kwargs)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\base\model.py", line 466, in fit
full_output=full_output)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\base\optimizer.py", line 191, in _fit
hess=hessian)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\base\optimizer.py", line 410, in _fit_lbfgs
**extra_kwargs)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\scipy\optimize\lbfgsb.py", line 193, in fmin_l_bfgs_b
**opts)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\scipy\optimize\lbfgsb.py", line 328, in _minimize_lbfgsb
f, g = func_and_grad(x)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\scipy\optimize\lbfgsb.py", line 273, in func_and_grad
f = fun(x, *args)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\scipy\optimize\optimize.py", line 292, in function_wrapper
return function(*(wrapper_args + args))
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\base\model.py", line 440, in f
return -self.loglike(params, *args) / nobs
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\tsa\statespace\mlemodel.py", line 646, in loglike
loglike = self.ssm.loglike(complex_step=complex_step, **kwargs)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\tsa\statespace\kalman_filter.py", line 825, in loglike
kfilter = self._filter(**kwargs)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\tsa\statespace\kalman_filter.py", line 747, in _filter
self._initialize_state(prefix=prefix, complex_step=complex_step)
File "C:\AppData\Local\Continuum\Anaconda3\lib\site-packages\statsmodels\tsa\statespace\representation.py", line 723, in _initialize_state
self._statespaces[prefix].initialize_stationary(complex_step)
File "_representation.pyx", line 1351, in statsmodels.tsa.statespace._representation.dStatespace.initialize_stationary
File "_tools.pyx", line 1151, in statsmodels.tsa.statespace._tools._dsolve_discrete_lyapunov
numpy.linalg.linalg.LinAlgError: LU decomposition error.