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Reconciliation raises an unexpected error #358

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mitchelloharawild opened this issue May 27, 2022 · 2 comments
Open

Reconciliation raises an unexpected error #358

mitchelloharawild opened this issue May 27, 2022 · 2 comments

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@mitchelloharawild
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First, this has nothing to do with the hts package. You are using the forecast reconcilation procedures in the fabletools package.

Second, your example consists of a single time series (the ACT), so the reconciliation is degenerate.

Third, SNAIVE is already reconciled since the forecasts are equal to the last year of data, so the reconciliation is degenerate.

That said, we should improve fabletools to prevent the error. @mitchelloharawild

To see it working on a small non-degenerate example, try this:

library(dplyr  , quietly = TRUE)
library(tsibble, quietly = TRUE)
library(fable  , quietly = TRUE)

tsibble::tourism %>%
  filter(State == 'ACT') %>% 
  aggregate_key(State / Region, Trips = sum(Trips)) %>% 
  model(base = fable::SNAIVE(Trips)) %>%
  reconcile(mint_cov = min_trace(base, method = "mint_cov")) %>% 
  forecast(h = 1)

From earowang/hts#43 (comment)
@MattCowgill
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I'm encountering this problem even with @robjhyndman's example code provided above (via earowang/hts#43 (comment)).

I've tried downgrading from fabletools 0.3.3.900 to 0.3.3 and get the same error.

library(dplyr  , quietly = TRUE)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(tsibble, quietly = TRUE)
#> 
#> Attaching package: 'tsibble'
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, union
library(fable  , quietly = TRUE)

tsibble::tourism %>%
  filter(State == 'ACT') %>% 
  aggregate_key(State / Region, Trips = sum(Trips)) %>% 
  model(base = fable::SNAIVE(Trips)) %>%
  reconcile(mint_cov = min_trace(base, method = "mint_cov")) %>% 
  forecast(h = 1)
#> Error in `mutate()`:
#> ℹ In argument: `mint_cov = (function (object, ...) ...`.
#> Caused by error:
#> ! min_trace needs covariance matrix to be positive definite.
#> Backtrace:
#>      ▆
#>   1. ├─... %>% forecast(h = 1)
#>   2. ├─generics::forecast(., h = 1)
#>   3. ├─fabletools:::forecast.mdl_df(., h = 1)
#>   4. │ └─dplyr::mutate_at(...)
#>   5. │   ├─dplyr::mutate(.tbl, !!!funs)
#>   6. │   └─dplyr:::mutate.data.frame(.tbl, !!!funs)
#>   7. │     └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
#>   8. │       ├─base::withCallingHandlers(...)
#>   9. │       └─dplyr:::mutate_col(dots[[i]], data, mask, new_columns)
#>  10. │         └─mask$eval_all_mutate(quo)
#>  11. │           └─dplyr (local) eval()
#>  12. ├─generics (local) `<fn>`(...)
#>  13. └─fabletools:::forecast.lst_mint_mdl(...)
#>  14.   └─rlang::abort(...)

Created on 2023-06-09 with reprex v2.0.2

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@MattCowgill
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I tried running some code from fpp chapter 11.4 - it worked as expected without error. No idea what's going on here...

library(fpp3)
#> ── Attaching packages ────────────────────────────────────────────── fpp3 0.5 ──
#> ✔ tibble      3.1.8     ✔ tsibble     1.1.3
#> ✔ dplyr       1.1.0     ✔ tsibbledata 0.4.1
#> ✔ tidyr       1.3.0     ✔ feasts      0.3.0
#> ✔ lubridate   1.9.2     ✔ fable       0.3.3
#> ✔ ggplot2     3.4.2     ✔ fabletools  0.3.3
#> ── Conflicts ───────────────────────────────────────────────── fpp3_conflicts ──
#> ✖ lubridate::date()    masks base::date()
#> ✖ dplyr::filter()      masks stats::filter()
#> ✖ tsibble::intersect() masks base::intersect()
#> ✖ tsibble::interval()  masks lubridate::interval()
#> ✖ dplyr::lag()         masks stats::lag()
#> ✖ tsibble::setdiff()   masks base::setdiff()
#> ✖ tsibble::union()     masks base::union()

tourism_full <- tourism |>
  aggregate_key((State/Region) * Purpose, Trips = sum(Trips))

fit <- tourism_full |>
  filter(year(Quarter) <= 2015) |>
  model(base = ETS(Trips)) |>
  reconcile(
    bu = bottom_up(base),
    ols = min_trace(base, method = "ols"),
    mint = min_trace(base, method = "mint_shrink")
  )

fc <- fit |> 
  forecast(h = "2 years")

fc |>
  filter(is_aggregated(Region), is_aggregated(Purpose)) |>
  autoplot(
    tourism_full |> filter(year(Quarter) >= 2011),
    level = NULL
  ) +
  labs(y = "Trips ('000)") +
  facet_wrap(vars(State), scales = "free_y")

Created on 2023-06-09 with reprex v2.0.2

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@MattCowgill @mitchelloharawild