readd(data_HDG) %>%
plot_time_series(date, value, .interactive = interactive)
readd(splits_HDG) %>%
tk_time_series_cv_plan() %>%
plot_time_series_cv_plan(date, value, .interactive = FALSE)
readd(models_tbl_HDG)
#> # Modeltime Table
#> # A tibble: 4 x 3
#> .model_id .model .model_desc
#> <int> <list> <chr>
#> 1 1 <fit[+]> ARIMA(0,1,0) WITH DRIFT
#> 2 2 <fit[+]> ARIMA(0,1,0) WITH DRIFT W/ XGBOOST ERRORS
#> 3 3 <fit[+]> ETS(M,AD,M)
#> 4 4 <fit[+]> PROPHET
readd(calibration_tbl_HDG)
#> # Modeltime Table
#> # A tibble: 4 x 5
#> .model_id .model .model_desc .type .calibration_data
#> <int> <list> <chr> <chr> <list>
#> 1 1 <fit[+]> ARIMA(0,1,0) WITH DRIFT Test <tibble [59 x 4]>
#> 2 2 <fit[+]> ARIMA(0,1,0) WITH DRIFT W/ XGBOOST ERRORS Test <tibble [59 x 4]>
#> 3 3 <fit[+]> ETS(M,AD,M) Test <tibble [59 x 4]>
#> 4 4 <fit[+]> PROPHET Test <tibble [59 x 4]>
readd(forecast_tbl_HDG) %>%
plot_modeltime_forecast(.legend_max_width = 25,
.interactive = interactive)
#> Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -Inf
readd(accuracy_tbl_HDG)$`_data`
#> # A tibble: 4 x 9
#> .model_id .model_desc .type mae mape mase smape rmse rsq
#> <int> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 ARIMA(0,1,0) WITH DRIFT Test 5.84 9.55 6.02 10.2 6.92 0.82
#> 2 2 ARIMA(0,1,0) WITH DRIFT W/ XGBOOST ERRORS Test 5.41 8.83 5.59 9.41 6.56 0.82
#> 3 3 ETS(M,AD,M) Test 7.3 11.9 7.54 13.0 8.75 0
#> 4 4 PROPHET Test 3.78 6.21 3.9 6.47 4.47 0.82
readd(two_week_fc_HDG)
#> # A tibble: 5 x 6
#> .ticker .index .value .low .high .model_desc
#> <chr> <date> <dbl> <dbl> <dbl> <chr>
#> 1 HDG 2022-01-03 63.9 56.5 71.3 PROPHET
#> 2 HDG 2022-01-04 64.2 56.8 71.6 PROPHET
#> 3 HDG 2022-01-05 64.4 57.0 71.8 PROPHET
#> 4 HDG 2022-01-06 64.6 57.2 72.0 PROPHET
#> 5 HDG 2022-01-07 64.8 57.4 72.2 PROPHET
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.