ARIMAX out of sample forecast with statsmodels
Please help me figure out how to do out of sample ARIMA forecast with 1 exogenous variable.
I have a list of list named FILEDATA
which contains two lists FILEDATA[0]
is the endogenous variable and FILEDATA[1]
is he exogenous variable data, they are both the same lenght.
I can do ARIMA forecast easily on FILEDATA[0]
, but when I add FILEDATA[1]
I can't figure out how to insert it in model_fit.forecast()
.
Read the documentation but it's very ambiguous, I don't understand what type the exog
parameter is in the model_fit.forecast()
function and in the ARIMA() I am also not sure how elements to supply.
I get errors like IndexError: tuple index out of range
, I am not sure what to do.
size = 4 # min 4
history = list(FILEDATA[0][0:size])
future = FILEDATA[0][size:len(FILEDATA[0])]
history2 = list(FILEDATA[1][0:size])
future2 = FILEDATA[1][size:len(FILEDATA[1])]
begintime = datetime.datetime.now()
predictions = list()
for t in range(len(future)):
model = ARIMA(endog=history, order=(1,1,0), exog=np.array(history2).reshape(len(history2),1) )
model_fit = model.fit(transparams=False, trend='nc',maxiter=20000 , tol=1e-08 , disp=0, method='mle')
actual2 = future2[t]
output = model_fit.forecast(exog=np.array(actual2))
forecast = output[0]
predictions.append(forecast)
actual = future[t]
history.append(actual)
history2.append(actual2)
print(t,'predicted=%f, actual=%f' % (forecast, actual))
endtime = datetime.datetime.now()
python-3.x numpy statistics statsmodels arima
add a comment |
Please help me figure out how to do out of sample ARIMA forecast with 1 exogenous variable.
I have a list of list named FILEDATA
which contains two lists FILEDATA[0]
is the endogenous variable and FILEDATA[1]
is he exogenous variable data, they are both the same lenght.
I can do ARIMA forecast easily on FILEDATA[0]
, but when I add FILEDATA[1]
I can't figure out how to insert it in model_fit.forecast()
.
Read the documentation but it's very ambiguous, I don't understand what type the exog
parameter is in the model_fit.forecast()
function and in the ARIMA() I am also not sure how elements to supply.
I get errors like IndexError: tuple index out of range
, I am not sure what to do.
size = 4 # min 4
history = list(FILEDATA[0][0:size])
future = FILEDATA[0][size:len(FILEDATA[0])]
history2 = list(FILEDATA[1][0:size])
future2 = FILEDATA[1][size:len(FILEDATA[1])]
begintime = datetime.datetime.now()
predictions = list()
for t in range(len(future)):
model = ARIMA(endog=history, order=(1,1,0), exog=np.array(history2).reshape(len(history2),1) )
model_fit = model.fit(transparams=False, trend='nc',maxiter=20000 , tol=1e-08 , disp=0, method='mle')
actual2 = future2[t]
output = model_fit.forecast(exog=np.array(actual2))
forecast = output[0]
predictions.append(forecast)
actual = future[t]
history.append(actual)
history2.append(actual2)
print(t,'predicted=%f, actual=%f' % (forecast, actual))
endtime = datetime.datetime.now()
python-3.x numpy statistics statsmodels arima
add a comment |
Please help me figure out how to do out of sample ARIMA forecast with 1 exogenous variable.
I have a list of list named FILEDATA
which contains two lists FILEDATA[0]
is the endogenous variable and FILEDATA[1]
is he exogenous variable data, they are both the same lenght.
I can do ARIMA forecast easily on FILEDATA[0]
, but when I add FILEDATA[1]
I can't figure out how to insert it in model_fit.forecast()
.
Read the documentation but it's very ambiguous, I don't understand what type the exog
parameter is in the model_fit.forecast()
function and in the ARIMA() I am also not sure how elements to supply.
I get errors like IndexError: tuple index out of range
, I am not sure what to do.
size = 4 # min 4
history = list(FILEDATA[0][0:size])
future = FILEDATA[0][size:len(FILEDATA[0])]
history2 = list(FILEDATA[1][0:size])
future2 = FILEDATA[1][size:len(FILEDATA[1])]
begintime = datetime.datetime.now()
predictions = list()
for t in range(len(future)):
model = ARIMA(endog=history, order=(1,1,0), exog=np.array(history2).reshape(len(history2),1) )
model_fit = model.fit(transparams=False, trend='nc',maxiter=20000 , tol=1e-08 , disp=0, method='mle')
actual2 = future2[t]
output = model_fit.forecast(exog=np.array(actual2))
forecast = output[0]
predictions.append(forecast)
actual = future[t]
history.append(actual)
history2.append(actual2)
print(t,'predicted=%f, actual=%f' % (forecast, actual))
endtime = datetime.datetime.now()
python-3.x numpy statistics statsmodels arima
Please help me figure out how to do out of sample ARIMA forecast with 1 exogenous variable.
I have a list of list named FILEDATA
which contains two lists FILEDATA[0]
is the endogenous variable and FILEDATA[1]
is he exogenous variable data, they are both the same lenght.
I can do ARIMA forecast easily on FILEDATA[0]
, but when I add FILEDATA[1]
I can't figure out how to insert it in model_fit.forecast()
.
Read the documentation but it's very ambiguous, I don't understand what type the exog
parameter is in the model_fit.forecast()
function and in the ARIMA() I am also not sure how elements to supply.
I get errors like IndexError: tuple index out of range
, I am not sure what to do.
size = 4 # min 4
history = list(FILEDATA[0][0:size])
future = FILEDATA[0][size:len(FILEDATA[0])]
history2 = list(FILEDATA[1][0:size])
future2 = FILEDATA[1][size:len(FILEDATA[1])]
begintime = datetime.datetime.now()
predictions = list()
for t in range(len(future)):
model = ARIMA(endog=history, order=(1,1,0), exog=np.array(history2).reshape(len(history2),1) )
model_fit = model.fit(transparams=False, trend='nc',maxiter=20000 , tol=1e-08 , disp=0, method='mle')
actual2 = future2[t]
output = model_fit.forecast(exog=np.array(actual2))
forecast = output[0]
predictions.append(forecast)
actual = future[t]
history.append(actual)
history2.append(actual2)
print(t,'predicted=%f, actual=%f' % (forecast, actual))
endtime = datetime.datetime.now()
python-3.x numpy statistics statsmodels arima
python-3.x numpy statistics statsmodels arima
asked Jan 2 at 5:56
johnyboy325johnyboy325
103
103
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