R Under development (unstable) (2026-03-02 r89513 ucrt) -- "Unsuffered Consequences"
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> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
> 
> library(testthat)
> library(beezdemand)
> 
> test_check("beezdemand")
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: zben
Param Space: log10
NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
Start values (first few): Q0_int=0.812, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: zben
Param Space: log10
NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
Start values (first few): Q0_int=0.812, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: zben
Param Space: log10
NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
Start values (first few): Q0_int=0.812, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Recoding 100 with 5.
A total of 1 outlying values were replaced
A total of 0 outlying values were replaced
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: zben
Param Space: log10
NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
Start values (first few): Q0_int=0.812, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: zben
Param Space: log10
NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
Start values (first few): Q0_int=0.812, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: zben
Param Space: log10
NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
Start values (first few): Q0_int=0.812, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Extended Summary of Empirical Demand Measures
=============================================

Data Overview:
  Number of subjects: 3
  Complete cases: 2 (66.7%)

Descriptive Statistics for Empirical Measures:
-----------------------------------------------

Intensity:
  Min: 8.00
  Median: 10.00
  Mean: 10.00
  Max: 12.00
  SD: 2.00

BP0:
  Min: 4.00
  Median: 4.00
  Mean: 4.00
  Max: 4.00
  SD: 0.00
  Missing: 1 (33.3%)

BP1:
  Min: 3.00
  Median: 3.00
  Mean: 3.33
  Max: 4.00
  SD: 0.58

Omaxe:
  Min: 8.00
  Median: 12.00
  Mean: 11.33
  Max: 14.00
  SD: 3.06

Pmaxe:
  Min: 2.00
  Median: 2.00
  Mean: 2.00
  Max: 2.00
  SD: 0.00
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: log10
NLME Formula: y ~ (10^Q0) * 10^(2 * (exp(-(10^alpha) * (10^Q0) * x) - 1))
Start values (first few): Q0_int=0.813, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: log10
NLME Formula: y ~ (10^Q0) * 10^(2 * (exp(-(10^alpha) * (10^Q0) * x) - 1))
Start values (first few): Q0_int=0.813, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: natural
NLME Formula: y ~ Q0 * 10^(2 * (exp(-alpha * Q0 * x) - 1))
Start values (first few): Q0_int=6.5, alpha_int=0.001
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: log10
NLME Formula: y ~ (10^Q0) * 10^(1.5 * (exp(-(10^alpha) * (10^Q0) * x) - 1))
Start values (first few): Q0_int=0.813, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: log10
NLME Formula: y ~ (10^Q0) * 10^(2.5 * (exp(-(10^alpha) * (10^Q0) * x) - 1))
Start values (first few): Q0_int=0.813, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: log10
NLME Formula: y ~ (10^Q0) * 10^(2 * (exp(-(10^alpha) * (10^Q0) * x) - 1))
Start values (first few): Q0_int=0.813, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: log10
NLME Formula: y ~ (10^Q0) * 10^(2 * (exp(-(10^alpha) * (10^Q0) * x) - 1))
Start values (first few): Q0_int=0.813, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: exponentiated
Param Space: log10
NLME Formula: y ~ (10^Q0) * 10^(2 * (exp(-(10^alpha) * (10^Q0) * x) - 1))
Start values (first few): Q0_int=0.813, alpha_int=-3
Number of fixed parameters: 4 (Q0: 2, alpha: 2)
Note: LRT assumes models are nested (reduced model is a special case of the full model). Nesting is not automatically verified. See ?compare_models for guidance on valid model comparisons.
Note: LRT assumes models are nested (reduced model is a special case of the full model). Nesting is not automatically verified. See ?compare_models for guidance on valid model comparisons.
Note: LRT assumes models are nested (reduced model is a special case of the full model). Nesting is not automatically verified. See ?compare_models for guidance on valid model comparisons.
Note: LRT assumes models are nested (reduced model is a special case of the full model). Nesting is not automatically verified. See ?compare_models for guidance on valid model comparisons.
Generating starting values using method: 'heuristic'
Using heuristic method for starting values.
--- Fitting NLME Model ---
Equation Form: zben
Param Space: log10
NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
Start values (first few): Q0_int=0.812, alpha_int=-3
Number of fixed parameters: 2 (Q0: 1, alpha: 1)
Note: LRT assumes models are nested (reduced model is a special case of the full model). Nesting is not automatically verified. See ?compare_models for guidance on valid model comparisons.
Free is shown as `0.01` for purposes of plotting.
Free is shown as `0.01` for purposes of plotting.
[ FAIL 0 | WARN 118 | SKIP 104 | PASS 1103 ]

══ Skipped tests (104) ═════════════════════════════════════════════════════════
• On CRAN (104): 'test-broom-contracts.R:5:3', 'test-broom-contracts.R:34:3',
  'test-broom-contracts.R:57:3', 'test-broom-contracts.R:82:3',
  'test-confint.R:78:3', 'test-confint.R:100:3', 'test-confint.R:128:3',
  'test-confint.R:171:3', 'test-confint.R:213:3', 'test-confint.R:240:3',
  'test-fit_demand_fixed.R:19:3', 'test-fit_demand_fixed.R:151:3',
  'test-fit_demand_fixed.R:462:3', 'test-fit_demand_fixed.R:539:3',
  'test-fit_demand_fixed.R:557:3', 'test-fit_demand_hurdle.R:4:3',
  'test-fit_demand_hurdle.R:31:3', 'test-fit_demand_hurdle.R:75:3',
  'test-fit_demand_hurdle.R:101:3', 'test-fit_demand_hurdle.R:146:3',
  'test-fit_demand_hurdle.R:170:3', 'test-fit_demand_hurdle.R:201:3',
  'test-fit_demand_hurdle.R:227:3', 'test-fit_demand_hurdle.R:247:3',
  'test-hurdle-alpha-component.R:2:3', 'test-hurdle_methods.R:4:3',
  'test-hurdle_methods.R:23:3', 'test-hurdle_methods.R:50:3',
  'test-hurdle_methods.R:73:3', 'test-hurdle_methods.R:100:3',
  'test-hurdle_methods.R:122:3', 'test-hurdle_methods.R:148:3',
  'test-hurdle_methods.R:171:3', 'test-hurdle_methods.R:196:3',
  'test-hurdle_methods.R:218:3', 'test-hurdle_part2_variants.R:68:3',
  'test-hurdle_part2_variants.R:123:3', 'test-hurdle_simulate.R:100:3',
  'test-hurdle_simulate.R:120:3', 'test-hurdle_simulate.R:148:3',
  'test-hurdle_simulate.R:163:3', 'test-hurdle_utils.R:66:3',
  'test-hurdle_utils.R:86:3', 'test-hurdle_utils.R:107:3',
  'test-hurdle_utils.R:157:3', 'test-hurdle_utils.R:179:3',
  'test-legacy-contracts.R:129:3', 'test-legacy-contracts.R:164:3',
  'test-legacy-contracts.R:223:3', 'test-legacy-fitcurves.R:92:3',
  'test-legacy-fitcurves.R:122:3', 'test-legacy-fitcurves.R:185:3',
  'test-legacy-fitmean.R:103:3', 'test-legacy-fitmean.R:123:3',
  'test-legacy-fitmean.R:206:3', 'test-legacy-fitmean.R:226:3',
  'test-param-space-report-space.R:9:3',
  'test-param-space-report-space.R:57:3',
  'test-param-space-report-space.R:98:3', 'test-plot-contracts.R:22:3',
  'test-plot_hurdle.R:4:3', 'test-plot_hurdle.R:24:3',
  'test-plot_hurdle.R:44:3', 'test-plot_hurdle.R:69:3',
  'test-plot_hurdle.R:93:3', 'test-plot_hurdle.R:117:3',
  'test-plot_hurdle.R:137:3', 'test-plot_hurdle.R:157:3',
  'test-predict-contracts.R:2:3', 'test-predict-contracts.R:33:3',
  'test-predict_fixed.R:2:3', 'test-predict_fixed.R:23:3',
  'test-predict_fixed.R:39:3', 'test-predict_fixed.R:55:3',
  'test-predict_fixed.R:67:3', 'test-predict_fixed.R:83:3',
  'test-summary-contracts.R:5:3', 'test-summary-contracts.R:63:3',
  'test_emms_comparisons.R:53:3', 'test_emms_comparisons.R:89:3',
  'test_emms_comparisons.R:132:3', 'test_emms_comparisons.R:160:3',
  'test_emms_comparisons.R:195:3', 'test_emms_comparisons.R:229:3',
  'test_emms_comparisons.R:265:3', 'test_emms_comparisons.R:301:3',
  'test_emms_comparisons.R:338:3', 'test_emms_comparisons.R:414:3',
  'test_fit_demand_mixed.R:236:3', 'test_fit_demand_mixed.R:255:3',
  'test_fit_demand_mixed.R:293:3', 'test_fit_demand_mixed.R:318:3',
  'test_fit_demand_mixed.R:357:3', 'test_fit_demand_mixed.R:391:3',
  'test_fit_demand_mixed.R:437:3', 'test_fit_demand_mixed.R:474:3',
  'test_fit_demand_mixed.R:505:3', 'test_fit_demand_mixed.R:532:3',
  'test_fit_demand_mixed.R:687:3', 'test_fit_demand_mixed.R:735:3',
  'test_fit_demand_mixed.R:769:3', 'test_fit_demand_mixed.R:794:3',
  'test_plot_individual_grid.R:2:3', 'test_plot_individual_grid.R:83:3'

[ FAIL 0 | WARN 118 | SKIP 104 | PASS 1103 ]
> 
> proc.time()
   user  system elapsed 
  76.79    4.06   81.07