Loading mkin Loading required package: testthat Testing mkin ✔ | OK F W S | Context ⠏ | 0 | Calculation of FOCUS chi2 error levels ⠋ | 1 | Calculation of FOCUS chi2 error levels ⠙ | 2 | Calculation of FOCUS chi2 error levels ✔ | 2 | Calculation of FOCUS chi2 error levels [2.2 s] ⠏ | 0 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠋ | 1 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠙ | 2 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠹ | 3 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠸ | 4 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠼ | 5 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠴ | 6 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠦ | 7 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ⠧ | 8 | Results for FOCUS D established in expertise for UBA (Ranke 2014) ✔ | 8 | Results for FOCUS D established in expertise for UBA (Ranke 2014) [6.5 s] ⠏ | 0 | Iteratively reweighted least squares (IRLS) fitting ⠋ | 0 1 | Iteratively reweighted least squares (IRLS) fitting ⠙ | 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠸ | 1 1 2 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠸ | 1 1 2 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠼ | 1 1 3 | Iteratively reweighted least squares (IRLS) fitting ⠴ | 1 1 4 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting ⠹ | 2 1 | Iteratively reweighted least squares (IRLS) fitting ⠸ | 3 1 | Iteratively reweighted least squares (IRLS) fitting ⠼ | 4 1 | Iteratively reweighted least squares (IRLS) fitting ⠴ | 5 1 | Iteratively reweighted least squares (IRLS) fitting ⠦ | 6 1 | Iteratively reweighted least squares (IRLS) fitting ⠧ | 7 1 | Iteratively reweighted least squares (IRLS) fitting ✖ | 7 1 | Iteratively reweighted least squares (IRLS) fitting [172.0 s] ──────────────────────────────────────────────────────────────────────────────── test_irls.R:38: error: Reweighting method 'obs' works Objekt 'tc_fit' nicht gefunden 1: mkinfit(m_synth_SFO_lin, SFO_lin_a, reweight.method = "obs", quiet = TRUE) at /home/jranke/git/mkin/tests/testthat/test_irls.R:38 2: system.time({ fit <- modFit(cost, c(state.ini.optim, transparms.optim), method = method.modFit, control = control.modFit, lower = lower, upper = upper, ...) if (!is.null(reweight.method)) { if (!reweight.method %in% c("obs", "tc")) stop("Only reweighting methods 'obs' and 'tc' are implemented") if (reweight.method == "obs") { if (!quiet) { cat("IRLS based on variance estimates for each observed variable\n") cat("Initial variance estimates are:\n") print(signif(fit$var_ms_unweighted, 8)) } } if (reweight.method == "tc") { tc_fit <- fit_error_model_mad_obs(cost(fit$par)$residuals, tc, 0) if (is.character(tc_fit)) { if (!quiet) { cat(tc_fit, ".\n", "No reweighting will be performed.") } tc_fitted <- c(sigma_low = NA, rsd_high = NA) } else { tc_fitted <- coef(tc_fit) if (!quiet) { cat("IRLS based on variance estimates according to the two component error model\n") cat("Initial variance components are:\n") print(signif(tc_fitted)) } } } reweight.diff = 1 n.iter <- 0 if (!is.null(err)) observed$err.ini <- observed[[err]] err = "err.irls" while (reweight.diff > reweight.tol & n.iter < reweight.max.iter & !is.character(tc_fit)) { n.iter <- n.iter + 1 if (reweight.method == "obs") { sr_old <- fit$var_ms_unweighted observed[err] <- sqrt(fit$var_ms_unweighted[as.character(observed$name)]) } if (reweight.method == "tc") { sr_old <- tc_fitted tmp_predicted <- mkin_wide_to_long(out_predicted, time = "time") tmp_data <- suppressMessages(join(observed, tmp_predicted, by = c("time", "name"))) observed[err] <- predict(tc_fit, newdata = data.frame(obs = observed$value)) } fit <- modFit(cost, fit$par, method = method.modFit, control = control.modFit, lower = lower, upper = upper, ...) if (reweight.method == "obs") { sr_new <- fit$var_ms_unweighted } if (reweight.method == "tc") { tc_fit <- fit_error_model_mad_obs(cost(fit$par)$residuals, tc_fitted, n.iter) if (is.character(tc_fit)) { if (!quiet) { cat(tc_fit, ".\n") } break } else { tc_fitted <- coef(tc_fit) sr_new <- tc_fitted } } reweight.diff = sum((sr_new - sr_old)^2) if (!quiet) { cat("Iteration", n.iter, "yields variance estimates:\n") print(signif(sr_new, 8)) cat("Sum of squared differences to last variance (component) estimates:", signif(reweight.diff, 2), "\n") } } } }) at /home/jranke/git/mkin/R/mkinfit.R:396 ──────────────────────────────────────────────────────────────────────────────── ⠏ | 0 | Model predictions with mkinpredict ⠋ | 1 | Model predictions with mkinpredict ⠙ | 2 | Model predictions with mkinpredict ⠹ | 3 | Model predictions with mkinpredict ✔ | 3 | Model predictions with mkinpredict [0.4 s] ⠏ | 0 | Fitting of parent only models ⠋ | 1 | Fitting of parent only models ⠙ | 2 | Fitting of parent only models ⠹ | 3 | Fitting of parent only models ⠸ | 4 | Fitting of parent only models ⠼ | 5 | Fitting of parent only models ⠴ | 6 | Fitting of parent only models ⠦ | 7 | Fitting of parent only models ⠧ | 8 | Fitting of parent only models ⠇ | 9 | Fitting of parent only models ⠏ | 10 | Fitting of parent only models ⠋ | 11 | Fitting of parent only models ⠙ | 12 | Fitting of parent only models ⠹ | 13 | Fitting of parent only models ⠸ | 14 | Fitting of parent only models ⠼ | 15 | Fitting of parent only models ⠴ | 16 | Fitting of parent only models ⠦ | 17 | Fitting of parent only models ⠧ | 18 | Fitting of parent only models ⠇ | 19 | Fitting of parent only models ⠏ | 20 | Fitting of parent only models ⠋ | 21 | Fitting of parent only models ✔ | 21 | Fitting of parent only models [22.1 s] ⠏ | 0 | Complex test case from Schaefer et al. (2007) Piacenza paper ⠋ | 1 | Complex test case from Schaefer et al. (2007) Piacenza paper ⠙ | 2 | Complex test case from Schaefer et al. (2007) Piacenza paper ✔ | 2 | Complex test case from Schaefer et al. (2007) Piacenza paper [5.2 s] ⠏ | 0 | Results for synthetic data established in expertise for UBA (Ranke 2014) ⠋ | 1 | Results for synthetic data established in expertise for UBA (Ranke 2014) ⠙ | 2 | Results for synthetic data established in expertise for UBA (Ranke 2014) ⠹ | 3 | Results for synthetic data established in expertise for UBA (Ranke 2014) ⠸ | 4 | Results for synthetic data established in expertise for UBA (Ranke 2014) ✔ | 4 | Results for synthetic data established in expertise for UBA (Ranke 2014) [6.5 s] ⠏ | 0 | Calculation of maximum time weighted average concentrations (TWAs) ⠋ | 1 | Calculation of maximum time weighted average concentrations (TWAs) ⠙ | 2 | Calculation of maximum time weighted average concentrations (TWAs) ⠹ | 3 | Calculation of maximum time weighted average concentrations (TWAs) ⠸ | 4 | Calculation of maximum time weighted average concentrations (TWAs) ⠼ | 5 | Calculation of maximum time weighted average concentrations (TWAs) ⠴ | 6 | Calculation of maximum time weighted average concentrations (TWAs) ⠦ | 7 | Calculation of maximum time weighted average concentrations (TWAs) ⠧ | 8 | Calculation of maximum time weighted average concentrations (TWAs) ✔ | 8 | Calculation of maximum time weighted average concentrations (TWAs) [7.6 s] ══ Results ═════════════════════════════════════════════════════════════════════ Duration: 222.6 s OK: 55 Failed: 1 Warnings: 0 Skipped: 0