Is ARIMA appropriate for time series prediction involving a mix of explanatory and independent variables?Underlying model for prediction using different prediction variablesTime series prediction using ARIMA vs LSTMFeature Selection, Machine learning and Time Series analysis, for large financial timeseriesSimple Time Series PredictionPredicting survival on Haberman's datasetIdeas for using polynomial regression for multivariate time series predictionpredicition for a specific monthTime Series Split on unequal number of samplesQualitative prediction based off data containing mixed qualitative and quantitative values?Time Series prediction for uneven data with some data provided
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Is ARIMA appropriate for time series prediction involving a mix of explanatory and independent variables?
Underlying model for prediction using different prediction variablesTime series prediction using ARIMA vs LSTMFeature Selection, Machine learning and Time Series analysis, for large financial timeseriesSimple Time Series PredictionPredicting survival on Haberman's datasetIdeas for using polynomial regression for multivariate time series predictionpredicition for a specific monthTime Series Split on unequal number of samplesQualitative prediction based off data containing mixed qualitative and quantitative values?Time Series prediction for uneven data with some data provided
$begingroup$
I have a table with the following columns:
Date(Month,Year), Sold_Past_Month, Quantity_Available, Quantity_Shipping_In, Missed_Sales, Quantity_Needed
Quantity_Needed is the dependent variable that is numerical.
I want to predict Quantity_Needed and train a model using the columns mentioned above; however, I also want Quantity_Needed to train the model.
I have data from the past 5 years -> so I would have roughly 60 rows of data for one item.
Is it possible to use ARIMA for this?
If it is, what should I do next to build my model?
machine-learning python r prediction
asked Apr 9 at 22:09
user9028381user9028381
111
$endgroup$
add a comment |
$begingroup$
I have a table with the following columns:
Date(Month,Year), Sold_Past_Month, Quantity_Available, Quantity_Shipping_In, Missed_Sales, Quantity_Needed
Quantity_Needed is the dependent variable that is numerical.
I want to predict Quantity_Needed and train a model using the columns mentioned above; however, I also want Quantity_Needed to train the model.
I have data from the past 5 years -> so I would have roughly 60 rows of data for one item.
Is it possible to use ARIMA for this?
If it is, what should I do next to build my model?
machine-learning python r prediction
asked Apr 9 at 22:09
user9028381user9028381
111
$endgroup$
$begingroup$
Hey! Welcome! Yes, ARIMA is actually constructed with time series in mind. If you are going to be successful is something you will only know if you try. You can go trough this tutorial for creating an ARIMA model with sklearn in Python.
$endgroup$
– Pedro Henrique Monforte
Apr 9 at 23:39
add a comment |
$begingroup$
I have a table with the following columns:
Date(Month,Year), Sold_Past_Month, Quantity_Available, Quantity_Shipping_In, Missed_Sales, Quantity_Needed
Quantity_Needed is the dependent variable that is numerical.
I want to predict Quantity_Needed and train a model using the columns mentioned above; however, I also want Quantity_Needed to train the model.
I have data from the past 5 years -> so I would have roughly 60 rows of data for one item.
Is it possible to use ARIMA for this?
If it is, what should I do next to build my model?
machine-learning python r prediction
asked Apr 9 at 22:09
user9028381user9028381
111
$endgroup$
I have a table with the following columns:
Date(Month,Year), Sold_Past_Month, Quantity_Available, Quantity_Shipping_In, Missed_Sales, Quantity_Needed
Quantity_Needed is the dependent variable that is numerical.
I want to predict Quantity_Needed and train a model using the columns mentioned above; however, I also want Quantity_Needed to train the model.
I have data from the past 5 years -> so I would have roughly 60 rows of data for one item.
Is it possible to use ARIMA for this?
If it is, what should I do next to build my model?
machine-learning python r prediction
machine-learning python r prediction
asked Apr 9 at 22:09
user9028381user9028381
111
asked Apr 9 at 22:09
user9028381user9028381
111
asked Apr 9 at 22:09
user9028381user9028381
111
asked Apr 9 at 22:09
user9028381user9028381
111
asked Apr 9 at 22:09
user9028381user9028381
111
111
$begingroup$
Hey! Welcome! Yes, ARIMA is actually constructed with time series in mind. If you are going to be successful is something you will only know if you try. You can go trough this tutorial for creating an ARIMA model with sklearn in Python.
$endgroup$
– Pedro Henrique Monforte
Apr 9 at 23:39
add a comment |
$begingroup$
Hey! Welcome! Yes, ARIMA is actually constructed with time series in mind. If you are going to be successful is something you will only know if you try. You can go trough this tutorial for creating an ARIMA model with sklearn in Python.
$endgroup$
– Pedro Henrique Monforte
Apr 9 at 23:39
$begingroup$
Hey! Welcome! Yes, ARIMA is actually constructed with time series in mind. If you are going to be successful is something you will only know if you try. You can go trough this tutorial for creating an ARIMA model with sklearn in Python.
$endgroup$
– Pedro Henrique Monforte
Apr 9 at 23:39
$begingroup$
Hey! Welcome! Yes, ARIMA is actually constructed with time series in mind. If you are going to be successful is something you will only know if you try. You can go trough this tutorial for creating an ARIMA model with sklearn in Python.
$endgroup$
– Pedro Henrique Monforte
Apr 9 at 23:39
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
The correct name of what you are looking for is: ARIMAX, the ARIMA model works without covariables, the X (exogenous variables) include the possibility of having other explanatory variables.
https://robjhyndman.com/hyndsight/arimax/
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
$endgroup$
add a comment |
$begingroup$
I am not sure about the nature of this problem because I see that even the independent variables are linked to their past values, if so and if you don’t have a test data set you can try VAR model.
In a VAR model, each variable is a linear function of the past values
of itself and the past values of all the other variables.
Otherwise you can also use LSTMs.
answered Apr 11 at 22:13
Cini09Cini09
166
$endgroup$
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
The correct name of what you are looking for is: ARIMAX, the ARIMA model works without covariables, the X (exogenous variables) include the possibility of having other explanatory variables.
https://robjhyndman.com/hyndsight/arimax/
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
$endgroup$
add a comment |
$begingroup$
The correct name of what you are looking for is: ARIMAX, the ARIMA model works without covariables, the X (exogenous variables) include the possibility of having other explanatory variables.
https://robjhyndman.com/hyndsight/arimax/
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
$endgroup$
add a comment |
$begingroup$
The correct name of what you are looking for is: ARIMAX, the ARIMA model works without covariables, the X (exogenous variables) include the possibility of having other explanatory variables.
https://robjhyndman.com/hyndsight/arimax/
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
$endgroup$
The correct name of what you are looking for is: ARIMAX, the ARIMA model works without covariables, the X (exogenous variables) include the possibility of having other explanatory variables.
https://robjhyndman.com/hyndsight/arimax/
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
answered Apr 11 at 15:34
Juan Esteban de la CalleJuan Esteban de la Calle
1,04322
1,04322
add a comment |
add a comment |
$begingroup$
I am not sure about the nature of this problem because I see that even the independent variables are linked to their past values, if so and if you don’t have a test data set you can try VAR model.
In a VAR model, each variable is a linear function of the past values
of itself and the past values of all the other variables.
Otherwise you can also use LSTMs.
answered Apr 11 at 22:13
Cini09Cini09
166
$endgroup$
add a comment |
$begingroup$
I am not sure about the nature of this problem because I see that even the independent variables are linked to their past values, if so and if you don’t have a test data set you can try VAR model.
In a VAR model, each variable is a linear function of the past values
of itself and the past values of all the other variables.
Otherwise you can also use LSTMs.
answered Apr 11 at 22:13
Cini09Cini09
166
$endgroup$
add a comment |
$begingroup$
I am not sure about the nature of this problem because I see that even the independent variables are linked to their past values, if so and if you don’t have a test data set you can try VAR model.
In a VAR model, each variable is a linear function of the past values
of itself and the past values of all the other variables.
Otherwise you can also use LSTMs.
answered Apr 11 at 22:13
Cini09Cini09
166
$endgroup$
I am not sure about the nature of this problem because I see that even the independent variables are linked to their past values, if so and if you don’t have a test data set you can try VAR model.
In a VAR model, each variable is a linear function of the past values
of itself and the past values of all the other variables.
Otherwise you can also use LSTMs.
answered Apr 11 at 22:13
Cini09Cini09
166
answered Apr 11 at 22:13
Cini09Cini09
166
answered Apr 11 at 22:13
Cini09Cini09
166
answered Apr 11 at 22:13
Cini09Cini09
166
166
add a comment |
add a comment |
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$begingroup$
Hey! Welcome! Yes, ARIMA is actually constructed with time series in mind. If you are going to be successful is something you will only know if you try. You can go trough this tutorial for creating an ARIMA model with sklearn in Python.
$endgroup$
– Pedro Henrique Monforte
Apr 9 at 23:39