Earlier I used to use from statsmodels.tsa.arima_model import ARIMA model = ARIMA(log_air_passengers, order=(2, 1, 0)) results_AR = model.fit(disp=-1) plt.p
library(readxl) export1 <- read_excel("C:/Users/Hazeeb/OneDrive/Desktop/data/export1.xlsx") View(export1) class(export1) #> [1] "tbl_df" "tbl"
My Data is in this format(Both Multiple and Multivariate Timeseries) I need to predict number of units sold is gonna be for every product across different st
I am using statsmodels.tsa.arima.model.ARIMA to fit an ARIMA model on a timeseries. How can I use this model to make predictions on unseen data? It seems that t