diff options
Diffstat (limited to 'tests/testthat/test_error_models.R')
-rw-r--r-- | tests/testthat/test_error_models.R | 17 |
1 files changed, 5 insertions, 12 deletions
diff --git a/tests/testthat/test_error_models.R b/tests/testthat/test_error_models.R index bda8ca7f..5a7aa4e8 100644 --- a/tests/testthat/test_error_models.R +++ b/tests/testthat/test_error_models.R @@ -1,4 +1,4 @@ -# Copyright (C) 2018 Johannes Ranke +# Copyright (C) 2018,2019 Johannes Ranke # Contact: jranke@uni-bremen.de # This file is part of the R package mkin @@ -70,13 +70,6 @@ test_that("Error model 'tc' works", { expect_equivalent(parms_3, c(102.1, 0.7393, 0.2992, 0.0202, 0.7687, 0.7229)) }) -test_that("Error model 'obs_tc' works", { - skip_on_cran() - fit_obs_tc_1 <- expect_warning(mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "obs_tc", quiet = TRUE), "NaN") - # Here the error model is overparameterised - expect_warning(summary(fit_obs_tc_1), "singular system") -}) - test_that("Reweighting method 'tc' produces reasonable variance estimates", { # I need to make the tc method more robust against that @@ -148,7 +141,7 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", { d_met_2_15 <- add_err(d_synth_DFOP_lin, sdfunc = function(x) sigma_twocomp(x, 0.5, 0.07), - n = 15, reps = 100, digits = 5, LOD = -Inf, seed = 123456) + n = 15, reps = 100, digits = 5, LOD = 0.01, seed = 123456) # For a single fit, we get a relative error of less than 10% in the error # model components @@ -165,14 +158,14 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", { parms_met_2_15_tc_e4 <- apply(sapply(f_met_2_15_tc_e4, function(x) x$bparms.optim), 1, mean) parm_errors_met_2_15_tc_e4 <- (parms_met_2_15_tc_e4[names(parms_DFOP_lin_optim)] - parms_DFOP_lin_optim) / parms_DFOP_lin_optim - expect_true(all(abs(parm_errors_met_2_15_tc_e4) < 0.01)) + expect_true(all(abs(parm_errors_met_2_15_tc_e4) < 0.015)) tcf_met_2_15_tc <- apply(sapply(f_met_2_15_tc_e4, function(x) x$errparms), 1, mean, na.rm = TRUE) tcf_met_2_15_tc_error_model_errors <- (tcf_met_2_15_tc - c(0.5, 0.07)) / c(0.5, 0.07) - # Here we get a precision < 15% for retrieving the original error model components + # Here we get a precision < 10% for retrieving the original error model components # from 15 datasets - expect_true(all(abs(tcf_met_2_15_tc_error_model_errors) < 0.15)) + expect_true(all(abs(tcf_met_2_15_tc_error_model_errors) < 0.10)) }) |