Hello,
I have started learning TS Forecasting in R and all the tutorials I went through focused on forecasting with one product with multiple time observations. I just need to see some examples where multiple product groups with multiple time observations to generate a forecast model with train and test data simulated. I have attached a sample data frame, could anyone please show me how to perform a full time series analysis with train/test split, fitting the model and generating point forecasts for the attached sample data frame. It would be really helpful.
``Data3<-structure(list(Prod_Category = c("Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "Acc",
"Acc", "Acc", "Acc", "Acc", "CT",
"CT", "CT", "CT", "CT", "CT", "CT",
"CT", "CT", "CT", "CT", "CT", "CT",
"CT", "CT", "CT", "CT", "CT", "CT",
"CT", "CT", "CT", "CT", "CT", "CT",
"CT", "CT", "CT", "CT", "CT", "CT",
"CT", "CT", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.A ", "E.A ", "E.A ", "E.A ",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.B",
"E.B", "E.B", "E.B", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.C", "E.C",
"E.C", "E.C", "E.D", "E.D",
"E.D", "E.D", "E.D", "E.D",
"E.D", "E.D", "E.D", "E.D",
"E.D", "E.D", "E.D", "E.D",
"E.D", "E.D", "E.D", "E.D",
"E.D", "E.D", "E.D", "E.D",
"E.D", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A", "L.A", "L.A",
"L.A", "L.A1", "L.A1", "L.A1",
"L.A1", "L.A1", "L.A1", "L.A1",
"L.A1", "L.A1", "L.A1", "L.A1",
"L.A1", "L.A1", "L.A1", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.B",
"L.B", "L.B", "L.B", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C", "L.C", "L.C", "L.C",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.C.B", "L.C.B", "L.C.B",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "L.S", "L.S",
"L.S", "L.S", "L.S", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.A", "R.A", "R.A", "R.A",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B",
"R.B", "R.B", "R.B", "R.B"
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"Week 49", "Week 50", "Week 52"), Sum.of.Shipment.Count = c(14,
28, 61, 59, 51, 63, 42, 52, 21, 70, 72, 51, 62, 62, 37, 58, 71,
39, 49, 44, 45, 63, 64, 59, 83, 13, 77, 74, 70, 24, 71, 39, 32,
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9, 16, 13, 19, 3, 13, 10, 17, 4, 2, 6, 5, 5, 8, 3, 4, 5, 4, 12,
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8, 4, 8, 7, 9, 8, 6, 15, 11, 12, 9, 10, 7, 6, 10, 11, 8, 7, 4,
8, 11, 2, 1, 1, 2, 3, 1, 2, 3, 3, 4, 1, 1, 3, 1, 2, 3, 1, 2,
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3, 2, 4, 1, 8, 4, 2, 1, 5, 1, 2, 4, 4, 2, 2, 4, 2, 2, 4, 4, 2,
2, 1)), row.names = c(NA, 608L), class = "data.frame")
``