CRAN Package Check Results for Package garchmodels

Last updated on 2021-11-01 00:49:39 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.1 17.25 205.55 222.80 WARN
r-devel-linux-x86_64-debian-gcc 0.1.1 13.22 180.07 193.29 OK
r-devel-linux-x86_64-fedora-clang 0.1.1 310.76 NOTE
r-devel-linux-x86_64-fedora-gcc 0.1.1 311.23 OK
r-devel-windows-x86_64 0.1.1 25.00 277.00 302.00 WARN
r-devel-windows-x86_64-gcc10-UCRT 0.1.1 WARN
r-patched-linux-x86_64 0.1.1 21.80 230.04 251.84 OK
r-patched-solaris-x86 0.1.1 282.40 NOTE
r-release-linux-x86_64 0.1.1 15.18 229.91 245.09 OK
r-release-macos-arm64 0.1.1 NOTE
r-release-macos-x86_64 0.1.1 WARN
r-release-windows-ix86+x86_64 0.1.1 27.00 219.00 246.00 NOTE
r-oldrel-macos-x86_64 0.1.1 WARN
r-oldrel-windows-ix86+x86_64 0.1.1 28.00 273.00 301.00 NOTE

Check Details

Version: 0.1.1
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'getting-started.Rmd' using rmarkdown
    Loading required package: parsnip
    Loading required package: rugarch
    Loading required package: parallel
    
    Attaching package: 'rugarch'
    
    The following object is masked from 'package:stats':
    
     sigma
    
    Loading required package: rmgarch
    -- Attaching packages -------------------------------------- tidymodels 0.1.4 --
    v broom 0.7.9 v rsample 0.1.0
    v dials 0.0.10 v tibble 3.1.5
    v dplyr 1.0.7 v tidyr 1.1.4
    v ggplot2 3.3.5 v tune 0.1.6
    v infer 1.0.0 v workflows 0.2.4
    v modeldata 0.1.1 v workflowsets 0.1.0
    v purrr 0.3.4 v yardstick 0.0.8
    v recipes 0.1.17
    -- Conflicts ----------------------------------------- tidymodels_conflicts() --
    x purrr::discard() masks scales::discard()
    x dplyr::filter() masks stats::filter()
    x dplyr::first() masks rmgarch::first()
    x dplyr::lag() masks stats::lag()
    x dplyr::last() masks rmgarch::last()
    x purrr::reduce() masks rugarch::reduce()
    x recipes::step() masks stats::step()
    * Search for functions across packages at https://www.tidymodels.org/find/
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
    v readr 2.0.2 v forcats 0.5.1
    v stringr 1.4.0
    -- Conflicts ------------------------------------------ tidyverse_conflicts() --
    x readr::col_factor() masks scales::col_factor()
    x purrr::discard() masks scales::discard()
    x dplyr::filter() masks stats::filter()
    x dplyr::first() masks rmgarch::first()
    x stringr::fixed() masks recipes::fixed()
    x dplyr::lag() masks stats::lag()
    x dplyr::last() masks rmgarch::last()
    x purrr::reduce() masks rugarch::reduce()
    x readr::spec() masks yardstick::spec()
    .date_var is missing. Using: date
    frequency = 5 observations per 1 week
    frequency = 5 observations per 1 week
    .date_var is missing. Using: date
    New names:
    * V1 -> V1...1
    * V1 -> V1...2
    New names:
    * V1 -> V1...3
    New names:
    * V1 -> V1...1
    * V1 -> V1...2
    New names:
    * V1 -> V1...3
    Warning in if (mmodel$model == "VAR") { :
     the condition has length > 1 and only the first element will be used
    Warning in if (mmodel$model == "constant") { :
     the condition has length > 1 and only the first element will be used
    --- finished re-building 'getting-started.Rmd'
    
    --- re-building 'tuning_univariate_algorithms.Rmd' using rmarkdown
    .date_var is missing. Using: date
    i Slice1: preprocessor 1/1
    v Slice1: preprocessor 1/1
    i Slice1: preprocessor 1/1, model 1/4
    frequency = 5 observations per 1 week
    x Slice1: preprocessor 1/1, model 1/4: Error: 'data' does not have 4 columns
    
    'dat...
    i Slice1: preprocessor 1/1
    v Slice1: preprocessor 1/1
    i Slice1: preprocessor 1/1, model 2/4
    
     *** caught segfault ***
    address 0x1, cause 'memory not mapped'
    
    Traceback:
     1: gc(FALSE)
     2: system.time(res$fit <- eval_mod(fit_call, capture = control$verbosity == 0, catch = control$catch, env = env, ...))
     3: form_form(object = object, env = env, control = control, ...)
     4: xy_form(object = object, env = eval_env, control = control, ...)
     5: fit_xy.model_spec(spec, x = mold$predictors, y = mold$outcomes, control = control_parsnip)
     6: fit_xy(spec, x = mold$predictors, y = mold$outcomes, control = control_parsnip)
     7: fit_from_xy(spec, mold, control_parsnip)
     8: fit.action_model(action_model, workflow = workflow, control = control)
     9: fit(action_model, workflow = workflow, control = control)
    10: .fit_model(workflow, control_workflow)
    11: withCallingHandlers(warning = add_cond, expr)
    12: doTryCatch(return(expr), name, parentenv, handler)
    13: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    14: tryCatchList(expr, classes, parentenv, handlers)
    15: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})
    16: try(withCallingHandlers(warning = add_cond, expr), silent = TRUE)
    17: catcher(expr)
    18: catch_and_log_fit(expr = .fit_model(workflow, control_workflow), control, split, iter_msg_model, notes = out_notes)
    19: fn(...)
    20: doTryCatch(return(expr), name, parentenv, handler)
    21: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    22: tryCatchList(expr, classes, parentenv, handlers)
    23: tryCatch(expr = list(result = fn(...), error = NULL, warnings = warnings), error = handle_error)
    24: withCallingHandlers(expr = tryCatch(expr = list(result = fn(...), error = NULL, warnings = warnings), error = handle_error), warning = handle_warning)
    25: safely_iterate(iteration, resamples, grid_info, workflow, metrics, control, seed)
    26: (function (fn, iteration, resamples, grid_info, workflow, metrics, control, seed) { safely_iterate <- super_safely(fn) result <- safely_iterate(iteration, resamples, grid_info, workflow, metrics, control, seed) error <- result$error warnings <- result$warnings result <- result$result if (is.null(error) && length(warnings) == 0L) { return(result) } if (is.null(error)) { res <- result notes <- result$.notes } else { res <- error notes <- NULL } problems <- list(res = res, signals = warnings) split <- resamples$splits[[iteration]] notes <- log_problems(notes, control, split, "internal", problems) if (!is.null(error)) { result <- list(.metrics = NULL, .extracts = NULL, .predictions = NULL, .all_outcome_names = list(), .notes = NULL) } result[[".notes"]] <- notes result})(fn = fn, ...)
    27: eval_tidy(call, mask)
    28: tune_grid_loop_iter_safely(iteration = iteration, resamples = resamples, grid_info = grid_info_row, workflow = workflow, metrics = metrics, control = control, seed = seed)
    29: eval(xpr, envir = envir)
    30: eval(xpr, envir = envir)
    31: doTryCatch(return(expr), name, parentenv, handler)
    32: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    33: tryCatchList(expr, classes, parentenv, handlers)
    34: tryCatch(eval(xpr, envir = envir), error = function(e) e)
    35: doTryCatch(return(expr), name, parentenv, handler)
    36: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    37: tryCatchList(expr, classes, parentenv, handlers)
    38: tryCatch({ repeat { args <- nextElem(it) if (obj$verbose) { cat(sprintf("evaluation # %d:\n", i)) print(args) } for (a in names(args)) assign(a, args[[a]], pos = envir, inherits = FALSE) r <- tryCatch(eval(xpr, envir = envir), error = function(e) e) if (obj$verbose) { cat("result of evaluating expression:\n") print(r) } tryCatch(accumulator(list(r), i), error = function(e) { cat("error calling combine function:\n") print(e) NULL }) i <- i + 1 }}, error = function(e) { if (!identical(conditionMessage(e), "StopIteration")) stop(simpleError(conditionMessage(e), expr))})
    39: e$fun(obj, substitute(ex), parent.frame(), e$data)
    40: foreach::foreach(iteration = iterations, .packages = packages, .errorhandling = "pass") %:% foreach::foreach(row = rows, seed = slice_seeds(seeds, iteration, n_grid_info), .packages = packages, .errorhandling = "pass", .combine = iter_combine) %op% { grid_info_row <- vctrs::vec_slice(grid_info, row) tune_grid_loop_iter_safely(iteration = iteration, resamples = resamples, grid_info = grid_info_row, workflow = workflow, metrics = metrics, control = control, seed = seed)}
    41: withCallingHandlers(expr, packageStartupMessage = function(c) tryInvokeRestart("muffleMessage"))
    42: suppressPackageStartupMessages(results <- foreach::foreach(iteration = iterations, .packages = packages, .errorhandling = "pass") %:% foreach::foreach(row = rows, seed = slice_seeds(seeds, iteration, n_grid_info), .packages = packages, .errorhandling = "pass", .combine = iter_combine) %op% { grid_info_row <- vctrs::vec_slice(grid_info, row) tune_grid_loop_iter_safely(iteration = iteration, resamples = resamples, grid_info = grid_info_row, workflow = workflow, metrics = metrics, control = control, seed = seed)})
    43: tune_grid_loop(resamples = resamples, grid = grid, workflow = workflow, metrics = metrics, control = control, rng = rng)
    44: tune_grid_workflow(object, resamples = resamples, grid = grid, metrics = metrics, pset = param_info, control = control)
    45: tune_grid.workflow(object = wflw, resamples = resamples, param_info = parameters(wflw), grid = 5, control = control_grid(verbose = TRUE, allow_par = TRUE, parallel_over = "everything"))
    46: tune_grid(object = wflw, resamples = resamples, param_info = parameters(wflw), grid = 5, control = control_grid(verbose = TRUE, allow_par = TRUE, parallel_over = "everything"))
    47: eval(expr, envir, enclos)
    48: eval(expr, envir, enclos)
    49: withVisible(eval(expr, envir, enclos))
    50: withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)
    51: handle(ev <- withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler, error = eHandler, message = mHandler))
    52: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)))
    53: evaluate_call(expr, parsed$src[[i]], envir = envir, enclos = enclos, debug = debug, last = i == length(out), use_try = stop_on_error != 2L, keep_warning = keep_warning, keep_message = keep_message, output_handler = output_handler, include_timing = include_timing)
    54: evaluate::evaluate(...)
    55: evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message), stop_on_error = if (is.numeric(options$error)) options$error else { if (options$error && options$include) 0L else 2L }, output_handler = knit_handlers(options$render, options))
    56: in_dir(input_dir(), evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message), stop_on_error = if (is.numeric(options$error)) options$error else { if (options$error && options$include) 0L else 2L }, output_handler = knit_handlers(options$render, options)))
    57: eng_r(options)
    58: block_exec(params)
    59: call_block(x)
    60: process_group.block(group)
    61: process_group(group)
    62: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) { setwd(wd) cat(res, sep = "\n", file = output %n% "") message("Quitting from lines ", paste(current_lines(i), collapse = "-"), " (", knit_concord$get("infile"), ") ") })
    63: process_file(text, output)
    64: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)
    65: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(), output_dir = getwd(), ...)
    66: vweave_rmarkdown(...)
    67: engine$weave(file, quiet = quiet, encoding = enc)
    68: doTryCatch(return(expr), name, parentenv, handler)
    69: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    70: tryCatchList(expr, classes, parentenv, handlers)
    71: tryCatch({ engine$weave(file, quiet = quiet, encoding = enc) setwd(startdir) output <- find_vignette_product(name, by = "weave", engine = engine) if (!have.makefile && vignette_is_tex(output)) { texi2pdf(file = output, clean = FALSE, quiet = quiet) output <- find_vignette_product(name, by = "texi2pdf", engine = engine) } outputs <- c(outputs, output)}, error = function(e) { thisOK <<- FALSE fails <<- c(fails, file) message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s", file, conditionMessage(e)))})
    72: tools:::buildVignettes(dir = "/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/garchmodels.Rcheck/vign_test/garchmodels")
    An irrecoverable exception occurred. R is aborting now ...
    Segmentation fault
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1.1
Check: installed package size
Result: NOTE
     installed size is 6.9Mb
     sub-directories of 1Mb or more:
     doc 6.5Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-x86_64, r-patched-solaris-x86, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-ix86+x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.1.1
Check: whether package can be installed
Result: WARN
    Found the following significant warnings:
     Warning: 'memory.limit()' is no longer supported
Flavors: r-devel-windows-x86_64, r-devel-windows-x86_64-gcc10-UCRT

Version: 0.1.1
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building ‘getting-started.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) not available. Falling back to R Markdown v1.
    Loading required package: parsnip
    Loading required package: rugarch
    Loading required package: parallel
    
    Attaching package: 'rugarch'
    
    The following object is masked from 'package:stats':
    
     sigma
    
    Loading required package: rmgarch
    ── Attaching packages ────────────────────────────────────── tidymodels 0.1.3 ──
    ✔ broom 0.7.6 ✔ rsample 0.1.0
    ✔ dials 0.0.9 ✔ tibble 3.1.2
    ✔ dplyr 1.0.6 ✔ tidyr 1.1.3
    ✔ ggplot2 3.3.3 ✔ tune 0.1.5
    ✔ infer 0.5.4 ✔ workflows 0.2.2
    ✔ modeldata 0.1.0 ✔ workflowsets 0.0.2
    ✔ purrr 0.3.4 ✔ yardstick 0.0.8
    ✔ recipes 0.1.16
    ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
    ✖ purrr::discard() masks scales::discard()
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ✖ recipes::step() masks stats::step()
    • Use tidymodels_prefer() to resolve common conflicts.
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
    ✔ readr 1.4.0 ✔ forcats 0.5.1
    ✔ stringr 1.4.0
    ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
    ✖ readr::col_factor() masks scales::col_factor()
    ✖ purrr::discard() masks scales::discard()
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ stringr::fixed() masks recipes::fixed()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ✖ readr::spec() masks yardstick::spec()
    .date_var is missing. Using: date
    frequency = 5 observations per 1 week
    frequency = 5 observations per 1 week
    .date_var is missing. Using: date
    New names:
    * V1 -> V1...1
    * V1 -> V1...2
    New names:
    * V1 -> V1...3
    New names:
    * V1 -> V1...1
    * V1 -> V1...2
    New names:
    * V1 -> V1...3
    Warning in if (mmodel$model == "VAR") { :
     the condition has length > 1 and only the first element will be used
    Warning in if (mmodel$model == "constant") { :
     the condition has length > 1 and only the first element will be used
    --- finished re-building ‘getting-started.Rmd’
    
    --- re-building ‘tuning_univariate_algorithms.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) not available. Falling back to R Markdown v1.
    Loading required package: parsnip
    Loading required package: rugarch
    Loading required package: parallel
    
    Attaching package: 'rugarch'
    
    The following object is masked from 'package:stats':
    
     sigma
    
    Loading required package: rmgarch
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
    ✔ ggplot2 3.3.3 ✔ purrr 0.3.4
    ✔ tibble 3.1.2 ✔ dplyr 1.0.6
    ✔ tidyr 1.1.3 ✔ stringr 1.4.0
    ✔ readr 1.4.0 ✔ forcats 0.5.1
    ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ── Attaching packages ────────────────────────────────────── tidymodels 0.1.3 ──
    ✔ broom 0.7.6 ✔ rsample 0.1.0
    ✔ dials 0.0.9 ✔ tune 0.1.5
    ✔ infer 0.5.4 ✔ workflows 0.2.2
    ✔ modeldata 0.1.0 ✔ workflowsets 0.0.2
    ✔ recipes 0.1.16 ✔ yardstick 0.0.8
    ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
    ✖ scales::discard() masks purrr::discard()
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ recipes::fixed() masks stringr::fixed()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ✖ yardstick::spec() masks readr::spec()
    ✖ recipes::step() masks stats::step()
    • Use tidymodels_prefer() to resolve common conflicts.
    .date_var is missing. Using: date
    PhantomJS not found. You can install it with webshot::install_phantomjs(). If it is installed, please make sure the phantomjs executable can be found via the PATH variable.
    PhantomJS not found. You can install it with webshot::install_phantomjs(). If it is installed, please make sure the phantomjs executable can be found via the PATH variable.
    Quitting from lines 94-103 (tuning_univariate_algorithms.Rmd)
    Error: processing vignette 'tuning_univariate_algorithms.Rmd' failed with diagnostics:
    invalid 'path' argument
    --- failed re-building ‘tuning_univariate_algorithms.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘tuning_univariate_algorithms.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-release-macos-x86_64

Version: 0.1.1
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building ‘getting-started.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Loading required package: parsnip
    Loading required package: rugarch
    Loading required package: parallel
    
    Attaching package: 'rugarch'
    
    The following object is masked from 'package:stats':
    
     sigma
    
    Loading required package: rmgarch
    ── Attaching packages ────────────────────────────────────── tidymodels 0.1.2 ──
    ✔ broom 0.7.6 ✔ recipes 0.1.15
    ✔ dials 0.0.9 ✔ rsample 0.0.9
    ✔ dplyr 1.0.5 ✔ tibble 3.1.0
    ✔ ggplot2 3.3.3 ✔ tidyr 1.1.3
    ✔ infer 0.5.4 ✔ tune 0.1.3
    ✔ modeldata 0.1.0 ✔ workflows 0.2.2
    ✔ purrr 0.3.4 ✔ yardstick 0.0.8
    ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
    ✖ purrr::discard() masks scales::discard()
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ✖ recipes::step() masks stats::step()
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
    ✔ readr 1.4.0 ✔ forcats 0.5.1
    ✔ stringr 1.4.0
    ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
    ✖ readr::col_factor() masks scales::col_factor()
    ✖ purrr::discard() masks scales::discard()
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ stringr::fixed() masks recipes::fixed()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ✖ readr::spec() masks yardstick::spec()
    .date_var is missing. Using: date
    frequency = 5 observations per 1 week
    frequency = 5 observations per 1 week
    .date_var is missing. Using: date
    New names:
    * V1 -> V1...1
    * V1 -> V1...2
    New names:
    * V1 -> V1...3
    New names:
    * V1 -> V1...1
    * V1 -> V1...2
    New names:
    * V1 -> V1...3
    Warning in if (mmodel$model == "VAR") { :
     the condition has length > 1 and only the first element will be used
    Warning in if (mmodel$model == "constant") { :
     the condition has length > 1 and only the first element will be used
    --- finished re-building ‘getting-started.Rmd’
    
    --- re-building ‘tuning_univariate_algorithms.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Loading required package: parsnip
    Loading required package: rugarch
    Loading required package: parallel
    
    Attaching package: 'rugarch'
    
    The following object is masked from 'package:stats':
    
     sigma
    
    Loading required package: rmgarch
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    Found more than one class "atomicVector" in cache; using the first, from namespace 'Matrix'
    Also defined by 'Rmpfr'
    ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
    ✔ ggplot2 3.3.3 ✔ purrr 0.3.4
    ✔ tibble 3.1.0 ✔ dplyr 1.0.5
    ✔ tidyr 1.1.3 ✔ stringr 1.4.0
    ✔ readr 1.4.0 ✔ forcats 0.5.1
    ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ── Attaching packages ────────────────────────────────────── tidymodels 0.1.2 ──
    ✔ broom 0.7.6 ✔ rsample 0.0.9
    ✔ dials 0.0.9 ✔ tune 0.1.3
    ✔ infer 0.5.4 ✔ workflows 0.2.2
    ✔ modeldata 0.1.0 ✔ yardstick 0.0.8
    ✔ recipes 0.1.15
    ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
    ✖ scales::discard() masks purrr::discard()
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::first() masks rmgarch::first()
    ✖ recipes::fixed() masks stringr::fixed()
    ✖ dplyr::lag() masks stats::lag()
    ✖ dplyr::last() masks rmgarch::last()
    ✖ purrr::reduce() masks rugarch::reduce()
    ✖ yardstick::spec() masks readr::spec()
    ✖ recipes::step() masks stats::step()
    .date_var is missing. Using: date
    PhantomJS not found. You can install it with webshot::install_phantomjs(). If it is installed, please make sure the phantomjs executable can be found via the PATH variable.
    Quitting from lines 94-103 (tuning_univariate_algorithms.Rmd)
    Error: processing vignette 'tuning_univariate_algorithms.Rmd' failed with diagnostics:
    invalid 'path' argument
    --- failed re-building ‘tuning_univariate_algorithms.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘tuning_univariate_algorithms.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-oldrel-macos-x86_64