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Simplify code for ensemble of simulated paths #1

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Aug 9, 2020
Merged

Simplify code for ensemble of simulated paths #1

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19 changes: 6 additions & 13 deletions README.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -94,23 +94,16 @@ Ensemble combining ETS and ARIMA sample paths

```{r ensemble, message=FALSE}
ensemble <- fit %>%
select(ETS, ARIMA) %>%
select(-SNAIVE) %>%
generate(times = 10000, h = "1 year") %>%
as_tibble() %>%
select(-.rep, -.model) %>%
nest(sample = -date) %>%
group_by(date) %>%
summarise(
.model = "ENSEMBLE",
sample = list(unname(unlist(sample)))
value = dist_sample(list(.sim)),
.mean = mean(value)
) %>%
ungroup() %>%
mutate(
value = dist_sample(sample),
.mean = mean(value),
) %>%
select(-sample) %>%
as_fable(index = date, key = ".model", distribution = value, response = "value")
.model = "ENSEMBLE"
) %>%
as_fable(distribution = value, response = "value")
```

CRPS calculations
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23 changes: 8 additions & 15 deletions README.md
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Expand Up @@ -83,23 +83,16 @@ Ensemble combining ETS and ARIMA sample paths

``` r
ensemble <- fit %>%
select(ETS, ARIMA) %>%
select(-SNAIVE) %>%
generate(times = 10000, h = "1 year") %>%
as_tibble() %>%
select(-.rep, -.model) %>%
nest(sample = -date) %>%
group_by(date) %>%
summarise(
.model = "ENSEMBLE",
sample = list(unname(unlist(sample)))
value = dist_sample(list(.sim)),
.mean = mean(value)
) %>%
ungroup() %>%
mutate(
value = dist_sample(sample),
.mean = mean(value),
) %>%
select(-sample) %>%
as_fable(index = date, key = ".model", distribution = value, response = "value")
.model = "ENSEMBLE"
) %>%
as_fable(distribution = value, response = "value")
#> Warning: The dimnames of the fable's distribution are missing and have been set
#> to match the response variables.
```
Expand All @@ -124,6 +117,6 @@ crps %>%
#> 1 SNAIVE Test 68.6 0
#> 2 ARIMA Test 32.9 52.0
#> 3 ETS Test 31.5 54.0
#> 4 ENSEMBLE Test 31.4 54.3
#> 5 COMBINATION Test 30.9 54.9
#> 4 COMBINATION Test 30.9 54.9
#> 5 ENSEMBLE Test 29.7 56.7
```
17 changes: 5 additions & 12 deletions quantile_ensembles.Rmd
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Expand Up @@ -156,21 +156,14 @@ For the Australian café data, we can combine 10000 simulated sample paths from
ensemble <- fit %>%
select(-SNAIVE) %>%
generate(times = 10000, h = "1 year") %>%
as_tibble() %>%
select(-.rep, -.model) %>%
nest(sample = -date) %>%
group_by(date) %>%
summarise(
.model = "ENSEMBLE",
sample = list(unname(unlist(sample)))
value = dist_sample(list(.sim)),
.mean = mean(value)
) %>%
ungroup() %>%
mutate(
value = dist_sample(sample),
.mean = mean(value),
) %>%
select(-sample) %>%
as_fable(index = date, key = ".model", distribution = value, response = "value")
.model = "ENSEMBLE"
) %>%
as_fable(distribution = value, response = "value")
ensemble %>%
accuracy(cafe, measures = list(CRPS = CRPS)) %>%
mutate(
Expand Down