CRAN Package Check Results for Package portvine

Last updated on 2025-12-19 14:50:30 CET.

Flavor	Version	T_install	T_check	T_total	Status
r-devel-linux-x86_64-debian-clang	1.0.3	101.34	397.68	499.02	OK
r-devel-linux-x86_64-debian-gcc	1.0.3	87.82	273.20	361.02	OK
r-devel-linux-x86_64-fedora-clang	1.0.3	169.00	620.55	789.55	OK
r-devel-linux-x86_64-fedora-gcc	1.0.3	235.00	333.03	568.03	ERROR
r-devel-windows-x86_64	1.0.3	114.00	377.00	491.00	OK
r-patched-linux-x86_64	1.0.3	124.76	382.89	507.65	OK
r-release-linux-x86_64	1.0.3	127.56	380.41	507.97	OK
r-release-macos-arm64	1.0.3				OK
r-release-macos-x86_64	1.0.3	70.00	348.00	418.00	OK
r-release-windows-x86_64	1.0.3	120.00	384.00	504.00	OK
r-oldrel-macos-arm64	1.0.3				NOTE
r-oldrel-macos-x86_64	1.0.3	66.00	224.00	290.00	NOTE
r-oldrel-windows-x86_64	1.0.3	147.00	524.00	671.00	NOTE

Check Details

Version: 1.0.3
Check: tests
Result: ERROR Running ‘testthat.R’ [137s/225s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(portvine) > data("sample_returns_small") > > test_check("portvine", reporter = "summary") S4accessors: WW1WW2 default_garch_spec: ........ dvine_ordering: .......... estimate_dependence_and_risk: SS estimate_marginal_models: ........................ estimate_risk_roll: .......................WW3. Fit marginal models: AAPL GOOG AMZN Fit vine copula models and estimate risk. Vine windows: (1/4) WW4S marginal_settings: ................ rcondvinecop: ............................. risk_measures: .................... utils: ..... vine_settings: ............. ══ Skipped ═════════════════════════════════════════════════════════════════════ 1. unconditional case ('test-estimate_dependence_and_risk.R:30:3') - Reason: On CRAN 2. conditional case ('test-estimate_dependence_and_risk.R:148:3') - Reason: On CRAN 3. parallel functionality ('test-estimate_risk_roll.R:558:3') - Reason: On CRAN ══ Warnings ════════════════════════════════════════════════════════════════════ 1. risk_estimates() basic functionality & input checks ('test-S4accessors.R:14:3') - Caught simpleError. Canceling all iterations ... 2. risk_estimates() basic functionality & input checks ('test-S4accessors.R:14:3') - Caught simpleError. Canceling all iterations ... 3. fitted_vines() & fitted_marginals() basic functionality ('test-S4accessors.R:312:3') - Caught simpleError. Canceling all iterations ... 4. fitted_vines() & fitted_marginals() basic functionality ('test-S4accessors.R:312:3') - Caught simpleError. Canceling all iterations ... 5. basic functionality (unconditionally) ('test-estimate_risk_roll.R:331:3') - Caught simpleError. Canceling all iterations ... 6. basic functionality (unconditionally) ('test-estimate_risk_roll.R:331:3') - Caught simpleError. Canceling all iterations ... 7. basic functionality (conditionally) ('test-estimate_risk_roll.R:449:3') - Caught simpleError. Canceling all iterations ... 8. basic functionality (conditionally) ('test-estimate_risk_roll.R:449:3') - Caught simpleError. Canceling all iterations ... ══ Failed ══════════════════════════════════════════════════════════════════════ ── 1. Error ('test-S4accessors.R:14:3'): risk_estimates() basic functionality & Error in ``[.data.table`(melt(copy(`_DT20`)[, `:=`(sample_id = seq(nrow(structure(list(AAPL = c(0.209526518594617, 0.888801740485287, 0.880086159491367, 0.982563181147936, 0.851817354623519, 0.327326762054149, 0.864145719693954, 0.9058113201714, 0.506971232891706, 0.104884515229914), AMZN = c(0.171110863125932, 0.413130016297171, 0.347645071950379, 0.520931748390738, 0.639416839798479, 0.249509386838978, 0.478589034472945, 0.990310112714462, 0.437671833052118, 0.0526139439824615), GOOG = c(0.719122365582734, 0.585058780387044, 0.867405500262976, 0.834015868371353, 0.762314558960497, 0.3776250469964, 0.728003450203687, 0.340336070163175, 0.58039515465498, 0.0901855339761823)), row.names = c(NA, -10L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x39f1c4a0>))))], measure.vars = c("AAPL", "AMZN", "GOOG"), variable.name = "asset", value.name = "sample", variable.factor = FALSE)[, `:=`(sample = trans_vals[["mu"]][trans_vals[["asset"]] == asset] + trans_vals[["sigma"]][trans_vals[["asset"]] == asset] * rugarch::qdist(distribution = trans_vals[["marg_dist"]][trans_vals[["asset"]] == asset], p = sample, skew = trans_vals[["skew"]][trans_vals[["asset"]] == asset], shape = trans_vals[["shape"]][trans_vals[["asset"]] == asset])), by = .(asset)], , `:=`(weight = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), dim = 4:3, dimnames = list(NULL, c("AAPL", "GOOG", "AMZN")))[1L, asset]), by = .(asset))`: attempt access index 3/3 in VECTOR_ELT Backtrace: ▆ 1. └─portvine::estimate_risk_roll(...) at test-S4accessors.R:14:3 2. └─portvine:::estimate_dependence_and_risk(...) 3. └─future.apply::future_lapply(...) 4. └─future.apply:::future_xapply(...) 5. └─base::tryCatch(...) 6. └─base (local) tryCatchList(expr, classes, parentenv, handlers) 7. └─base (local) tryCatchOne(...) 8. └─value[[3L]](cond) 9. └─future.apply:::onError(e, futures = fs, debug = debug) ── 2. Error ('test-S4accessors.R:312:3'): fitted_vines() & fitted_marginals() ba Error in ``[.data.table`(melt(copy(`_DT40`)[, `:=`(sample_id = seq(nrow(structure(list(AAPL = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.727447098696852, 0.727447098696852, 0.727447098696852, 0.727447098696852, 0.727447098696852, 0.727447098696852, 0.727447098696852, 0.727447098696852, 0.727447098696852, 0.727447098696852), AMZN = c(0.444866215751782, 0.628593477283579, 0.520855319984916, 0.156222642167859, 0.553944506416007, 0.777213271501424, 0.398388293741356, 0.47505402040871, 0.509443814204446, 0.384254462128248, 0.407129909701973, 0.484859761166073, 0.192622567955219, 0.16835877792208, 0.738648191114862, 0.814797735537648, 0.294067885505825, 0.25719934846251, 0.840337610427712, 0.530428837903932), GOOG = c(0.311061521802173, 0.520483637116283, 0.737218004132263, 0.362397672958788, 0.79210034775356, 0.784367600471135, 0.474584164317475, 0.716676449213835, 0.758024230334118, 0.643883593599405, 0.58079529751331, 0.647216157711304, 0.3471484341708, 0.15752329822806, 0.70369533616663, 0.586169478934378, 0.344716040724017, 0.300914784812098, 0.690035567183748, 0.634055257675292)), row.names = c(NA, -20L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x39f1c4a0>))))], measure.vars = c("AAPL", "AMZN", "GOOG"), variable.name = "asset", value.name = "sample", variable.factor = FALSE)[, `:=`(sample = trans_vals[["mu"]][trans_vals[["asset"]] == asset] + trans_vals[["sigma"]][trans_vals[["asset"]] == asset] * rugarch::qdist(distribution = trans_vals[["marg_dist"]][trans_vals[["asset"]] == asset], p = sample, skew = trans_vals[["skew"]][trans_vals[["asset"]] == asset], shape = trans_vals[["shape"]][trans_vals[["asset"]] == asset])), by = .(asset)], , `:=`(weight = structure(c(0, 0, 1, 1, 1, 1), dim = 2:3, dimnames = list(NULL, c("AAPL", "GOOG", "AMZN")))[1L, asset]), by = .(asset))`: attempt access index 3/3 in VECTOR_ELT Backtrace: ▆ 1. └─portvine::estimate_risk_roll(...) at test-S4accessors.R:312:3 2. └─portvine:::estimate_dependence_and_risk(...) 3. └─future.apply::future_lapply(...) 4. └─future.apply:::future_xapply(...) 5. └─base::tryCatch(...) 6. └─base (local) tryCatchList(expr, classes, parentenv, handlers) 7. └─base (local) tryCatchOne(...) 8. └─value[[3L]](cond) 9. └─future.apply:::onError(e, futures = fs, debug = debug) ── 3. Error ('test-estimate_risk_roll.R:331:3'): basic functionality (unconditio Error in ``[.data.table`(melt(copy(`_DT128`)[, `:=`(sample_id = seq(nrow(structure(list(AAPL = c(0.316017737483609, 0.984920103473055, 0.616457431950822, 0.546045223958843, 0.0460986991532727, 0.706085798114056, 0.0205603667530673, 0.10892143728145, 0.688835805351214, 0.611960919412703), AMZN = c(0.190530428182826, 0.558974788455794, 0.881708455507389, 0.298013812668616, 0.0957197921039991, 0.427908683264522, 0.144343779480111, 0.764404012126395, 0.776145371201081, 0.840432336231161), GOOG = c(0.126073424238712, 0.465829518157989, 0.742902743397281, 0.333654104731977, 0.0120420018211007, 0.272319915238768, 0.00978341395966709, 0.625954698538408, 0.569327579112723, 0.333761575864628)), row.names = c(NA, -10L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x39f1c4a0>))))], measure.vars = c("AAPL", "AMZN", "GOOG"), variable.name = "asset", value.name = "sample", variable.factor = FALSE)[, `:=`(sample = trans_vals[["mu"]][trans_vals[["asset"]] == asset] + trans_vals[["sigma"]][trans_vals[["asset"]] == asset] * rugarch::qdist(distribution = trans_vals[["marg_dist"]][trans_vals[["asset"]] == asset], p = sample, skew = trans_vals[["skew"]][trans_vals[["asset"]] == asset], shape = trans_vals[["shape"]][trans_vals[["asset"]] == asset])), by = .(asset)], , `:=`(weight = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), dim = 4:3, dimnames = list(NULL, c("AAPL", "GOOG", "AMZN")))[1L, asset]), by = .(asset))`: attempt access index 3/3 in VECTOR_ELT Backtrace: ▆ 1. └─portvine::estimate_risk_roll(...) at test-estimate_risk_roll.R:331:3 2. └─portvine:::estimate_dependence_and_risk(...) 3. └─future.apply::future_lapply(...) 4. └─future.apply:::future_xapply(...) 5. └─base::tryCatch(...) 6. └─base (local) tryCatchList(expr, classes, parentenv, handlers) 7. └─base (local) tryCatchOne(...) 8. └─value[[3L]](cond) 9. └─future.apply:::onError(e, futures = fs, debug = debug) ── 4. Error ('test-estimate_risk_roll.R:449:3'): basic functionality (conditiona Error in ``[.data.table`(melt(copy(`_DT148`)[, `:=`(sample_id = seq(nrow(structure(list(AAPL = c(0.0521097794712437, 0.0457964223086946, 0.00640723535007526, 0.382560855578069, 0.388009270394654, 0.0182644498775305, 0.998658854776191, 0.0565972795053729, 0.544422455653062, 0.0849078667134904, 0.422868781326148, 0.67725439700215, 0.82571413233788, 0.985152530979974, 0.954835187647013, 0.49481362453126, 0.455316346367263, 0.234017881147352, 0.544291014828739, 0.564694186098919, 0.146658953906134, 0.643361299392134, 0.37363677394706, 0.763151489204603, 0.352505876189958, 0.478443762560652, 0.291368700119701, 0.761586188810779, 0.825929654963075, 0.639989906752788, 0.460761545834917, 0.891116650296842, 0.913862712288067), AMZN = c(0.090486280940577, 0.083564726359194, 0.0282303647368748, 0.0632207038088541, 0.566266436349274, 0.0291773090197369, 0.535153081258915, 0.0305919759434213, 0.215770669138778, 0.0629827078234699, 0.339614405764356, 0.856401403756023, 0.617636711208802, 0.582300403600638, 0.958777111989064, 0.45080054176498, 0.241327265066479, 0.598577492363748, 0.469945257030295, 0.933513443739573, 0.514584199848292, 0.171974737152868, 0.948132457634868, 0.623369315065158, 0.684340401846625, 0.630598956273145, 0.261470170390827, 0.450934506641964, 0.825286874133172, 0.252728002384227, 0.569850002999883, 0.575907441988026, 0.897178524131068), GOOG = c(0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784, 0.60420106897784)), row.names = c(NA, -33L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x39f1c4a0>))))], measure.vars = c("AAPL", "AMZN", "GOOG"), variable.name = "asset", value.name = "sample", variable.factor = FALSE)[, `:=`(sample = trans_vals[["mu"]][trans_vals[["asset"]] == asset] + trans_vals[["sigma"]][trans_vals[["asset"]] == asset] * rugarch::qdist(distribution = trans_vals[["marg_dist"]][trans_vals[["asset"]] == asset], p = sample, skew = trans_vals[["skew"]][trans_vals[["asset"]] == asset], shape = trans_vals[["shape"]][trans_vals[["asset"]] == asset])), by = .(asset)], , `:=`(weight = structure(c(1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1), dim = 4:3, dimnames = list(NULL, c("AAPL", "GOOG", "AMZN")))[1L, asset]), by = .(asset))`: attempt access index 3/3 in VECTOR_ELT Backtrace: ▆ 1. └─portvine::estimate_risk_roll(...) at test-estimate_risk_roll.R:449:3 2. └─portvine:::estimate_dependence_and_risk(...) 3. └─future.apply::future_lapply(...) 4. └─future.apply:::future_xapply(...) 5. └─base::tryCatch(...) 6. └─base (local) tryCatchList(expr, classes, parentenv, handlers) 7. └─base (local) tryCatchOne(...) 8. └─value[[3L]](cond) 9. └─future.apply:::onError(e, futures = fs, debug = debug) ══ DONE ════════════════════════════════════════════════════════════════════════ Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 1.0.3
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building ‘get_started.Rmd’ using rmarkdown Quitting from get_started.Rmd:142-157 [unnamed-chunk-9] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <error/rlang_error> Error in `[.data.table`: ! attempt access index 3/3 in VECTOR_ELT --- Backtrace: ▆ 1. └─portvine::estimate_risk_roll(...) 2. └─portvine:::estimate_dependence_and_risk(...) 3. └─future.apply::future_lapply(...) 4. └─future.apply:::future_xapply(...) 5. └─base::tryCatch(...) 6. └─base (local) tryCatchList(expr, classes, parentenv, handlers) 7. └─base (local) tryCatchOne(...) 8. └─value[[3L]](cond) 9. └─future.apply:::onError(e, futures = fs, debug = debug) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Error: processing vignette 'get_started.Rmd' failed with diagnostics: attempt access index 3/3 in VECTOR_ELT --- failed re-building ‘get_started.Rmd’ SUMMARY: processing the following file failed: ‘get_started.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 1.0.3
Check: installed package size
Result: NOTE installed size is 39.8Mb sub-directories of 1Mb or more: libs 38.6Mb Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64