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I'm playing with sweep and I'm struggling in how to forecast multiple models for each time series in the tibble. I have read the vignettes and this topic it's treated separately and I haven't been able to merge both ideas.
Here is a reproducible example:
library(forecast)
library(tidyquant)
library(timetk)
library(sweep)
monthly_qty_by_cat2_ts <- bike_sales %>%
mutate(order.month = as_date(as.yearmon(order.date))) %>%
group_by(category.secondary, order.month) %>%
summarise(total.qty = sum(quantity)) %>%
group_by(category.secondary) %>%
nest(.key = "data.tbl") %>%
mutate(data.ts = map(.x = data.tbl,
.f = tk_ts,
select = -order.month,
start = 2011,
freq = 12))
# Time Series forecasting
monthly_qty_by_cat2_fit <- monthly_qty_by_cat2_ts %>%
mutate(fit.ets = map(data.ts, ets))
monthly_qty_by_cat2_fit
# Output
# A tibble: 9 x 4
category.secondary data.tbl data.ts fit.ets
<chr> <list> <list> <list>
1 Cross Country Race <tibble [60 x 2]> <S3: ts> <S3: ets>
2 Cyclocross <tibble [60 x 2]> <S3: ts> <S3: ets>
3 Elite Road <tibble [60 x 2]> <S3: ts> <S3: ets>
4 Endurance Road <tibble [60 x 2]> <S3: ts> <S3: ets>
5 Fat Bike <tibble [58 x 2]> <S3: ts> <S3: ets>
6 Over Mountain <tibble [60 x 2]> <S3: ts> <S3: ets>
7 Sport <tibble [60 x 2]> <S3: ts> <S3: ets>
8 Trail <tibble [60 x 2]> <S3: ts> <S3: ets>
9 Triathalon <tibble [60 x 2]> <S3: ts> <S3: ets>
One solutions would be the following one but I belive that there exist a better way to do that
What I'm trying to do is forecast different models as it's done in the vignette SW02_Forecasting_Multiple_Models but here the list of models has the data "hardcoded" and then it's just executed with invoke_map.
How it could be modified to be able to forecast multiple models?
The text was updated successfully, but these errors were encountered:
Hi,
I'm playing with sweep and I'm struggling in how to forecast multiple models for each time series in the tibble. I have read the vignettes and this topic it's treated separately and I haven't been able to merge both ideas.
Here is a reproducible example:
One solutions would be the following one but I belive that there exist a better way to do that
What I'm trying to do is forecast different models as it's done in the vignette SW02_Forecasting_Multiple_Models but here the list of models has the data "hardcoded" and then it's just executed with
invoke_map
.How it could be modified to be able to forecast multiple models?
The text was updated successfully, but these errors were encountered: