CRAN Package Check Results for Package fable.bayesRecon

Last updated on 2026-09-16 05:50:57 CEST.

Flavor	Version	Tinstall	Tcheck	Ttotal	Status	Flags
r-devel-linux-x86_64-debian-clang	0.2.1	9.45	235.30	244.75	OK
r-devel-linux-x86_64-debian-gcc	0.2.1	5.77	161.65	167.42	OK
r-devel-linux-x86_64-fedora-clang	0.2.1			155.53	OK
r-devel-linux-x86_64-fedora-gcc	0.2.1			169.20	OK
r-devel-windows-x86_64	0.2.0	11.00	241.00	252.00	ERROR
r-patched-linux-x86_64	0.2.0	9.53	219.39	228.92	ERROR
r-release-linux-x86_64	0.2.1	9.42	222.35	231.77	OK
r-release-macos-arm64	0.2.0	2.00	68.00	70.00	OK
r-release-macos-x86_64	0.2.1	6.00	272.00	278.00	OK
r-release-windows-x86_64	0.2.1	12.00	236.00	248.00	OK
r-oldrel-macos-arm64	0.2.1	2.00	73.00	75.00	OK
r-oldrel-macos-x86_64	0.2.1	6.00	287.00	293.00	OK
r-oldrel-windows-x86_64	0.2.1	17.00	306.00	323.00	OK

Check Details

Version: 0.2.0
Check: examples
Result: ERROR Running examples in 'fable.bayesRecon-Ex.R' failed The error most likely occurred in: > ### Name: bayesRecon_MixCond > ### Title: Probabilistic reconciliation of mixed hierarchies > ### Aliases: bayesRecon_MixCond bayesRecon_TDcond > > ### ** Examples > > library(tsibble) Attaching package: 'tsibble' The following objects are masked from 'package:base': intersect, setdiff, union > library(dplyr) 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(fable) Loading required package: fabletools > library(fabletools) > library(fable.intermittent) > > > # Mixed hierarchy with integer-valued bottom and one upper aggregate, from the `auto` dataset. > # Forecasts with EMPDISTR for bottom base and ETS for smooth base forecasts. > > > # Helper: split a hierarchy into its upper (aggregated) and bottom (leaf) series so that a > # different base model can be fitted at each level. > hier_filter <- function(data, level = c("upper", "bottom")) { + level <- match.arg(level) + key_cols <- tsibble::key_vars(data) + if (level == "upper") { + dplyr::filter(data, dplyr::if_any(dplyr::all_of(key_cols), fabletools::is_aggregated)) + } else { + dplyr::filter(data, !dplyr::if_any(dplyr::all_of(key_cols), fabletools::is_aggregated)) + } + } > > # Build a small two-level hierarchy from a handful of auto spare-part series. > # The four series become the bottom level; their sum is the upper aggregate. > sel <- c("TS1461", "TS2953", "TS333", "TS2710") > data <- auto |> + dplyr::filter(series_id %in% sel) |> + fabletools::aggregate_key(series_id, value = sum(value)) > > > # Hold out the last 6 months for forecasting. > train <- data |> dplyr::filter(index < tsibble::yearmonth("2011 Jul")) > > # Base forecasts: a smooth (Gaussian) model on the continuous-looking upper aggregate, > # and the EMPDISTR non-parametric count model on the intermittent bottom series. > fit_upper <- train |> + hier_filter("upper") |> + fabletools::model(base = fable::ETS(value)) > > fit_bottom <- train |> + hier_filter("bottom") |> + fabletools::model(base = fable.intermittent::EMPDISTR(value)) Error: 'EMPDISTR' is not an exported object from 'namespace:fable.intermittent' Execution halted Flavor: r-devel-windows-x86_64

Version: 0.2.0
Check: examples
Result: ERROR Running examples in ‘fable.bayesRecon-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: bayesRecon_MixCond > ### Title: Probabilistic reconciliation of mixed hierarchies > ### Aliases: bayesRecon_MixCond bayesRecon_TDcond > > ### ** Examples > > library(tsibble) Attaching package: ‘tsibble’ The following objects are masked from ‘package:base’: intersect, setdiff, union > library(dplyr) 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(fable) Loading required package: fabletools > library(fabletools) > library(fable.intermittent) > > > # Mixed hierarchy with integer-valued bottom and one upper aggregate, from the `auto` dataset. > # Forecasts with EMPDISTR for bottom base and ETS for smooth base forecasts. > > > # Helper: split a hierarchy into its upper (aggregated) and bottom (leaf) series so that a > # different base model can be fitted at each level. > hier_filter <- function(data, level = c("upper", "bottom")) { + level <- match.arg(level) + key_cols <- tsibble::key_vars(data) + if (level == "upper") { + dplyr::filter(data, dplyr::if_any(dplyr::all_of(key_cols), fabletools::is_aggregated)) + } else { + dplyr::filter(data, !dplyr::if_any(dplyr::all_of(key_cols), fabletools::is_aggregated)) + } + } > > # Build a small two-level hierarchy from a handful of auto spare-part series. > # The four series become the bottom level; their sum is the upper aggregate. > sel <- c("TS1461", "TS2953", "TS333", "TS2710") > data <- auto |> + dplyr::filter(series_id %in% sel) |> + fabletools::aggregate_key(series_id, value = sum(value)) > > > # Hold out the last 6 months for forecasting. > train <- data |> dplyr::filter(index < tsibble::yearmonth("2011 Jul")) > > # Base forecasts: a smooth (Gaussian) model on the continuous-looking upper aggregate, > # and the EMPDISTR non-parametric count model on the intermittent bottom series. > fit_upper <- train |> + hier_filter("upper") |> + fabletools::model(base = fable::ETS(value)) > > fit_bottom <- train |> + hier_filter("bottom") |> + fabletools::model(base = fable.intermittent::EMPDISTR(value)) Error: 'EMPDISTR' is not an exported object from 'namespace:fable.intermittent' Execution halted Flavor: r-patched-linux-x86_64