From 082be7baa35d7e8131a70ca8cc061d90e08fa584 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 15 Apr 2020 01:27:02 +0200 Subject: A plot method for nlme.mmkin fits --- docs/reference/nlme.html | 32 +++++++++++++++++--------------- 1 file changed, 17 insertions(+), 15 deletions(-) (limited to 'docs/reference/nlme.html') diff --git a/docs/reference/nlme.html b/docs/reference/nlme.html index 1b05f882..981845fe 100644 --- a/docs/reference/nlme.html +++ b/docs/reference/nlme.html @@ -6,7 +6,7 @@ -Estimation of parameter distributions from mmkin row objects — nlme_function • mkin +Helper functions to create nlme models from mmkin row objects — nlme_function • mkin @@ -35,7 +35,7 @@ - +
-

Estimation of parameter distributions from mmkin row objects

+

Helper functions to create nlme models from mmkin row objects

@@ -255,37 +255,39 @@ datasets.

nlme_f_sfo_sfo <- nlme_function(f_2["SFO-SFO", ]) nlme_f_sfo_sfo_ff <- nlme_function(f_2["SFO-SFO-ff", ]) nlme_f_fomc_sfo <- nlme_function(f_2["FOMC-SFO", ]) + assign("nlme_f_sfo_sfo", nlme_f_sfo_sfo, globalenv()) + assign("nlme_f_sfo_sfo_ff", nlme_f_sfo_sfo_ff, globalenv()) + assign("nlme_f_fomc_sfo", nlme_f_fomc_sfo, globalenv()) - # Allowing for correlations between random effects leads to non-convergence + # Allowing for correlations between random effects (not shown) + # leads to non-convergence f_nlme_sfo_sfo <- nlme(value ~ nlme_f_sfo_sfo(name, time, parent_0, log_k_parent_sink, log_k_parent_A1, log_k_A1_sink), data = grouped_data_2, fixed = parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1, random = pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1), - start = mean_dp_sfo_sfo)
#> Error in nlme_f_sfo_sfo(name, time, parent_0, log_k_parent_sink, log_k_parent_A1, log_k_A1_sink): konnte Funktion "nlme_f_sfo_sfo" nicht finden
+ start = mean_dp_sfo_sfo) + # augPred does not see to work on this object, so no plot is shown + # The same model fitted with transformed formation fractions does not converge f_nlme_sfo_sfo_ff <- nlme(value ~ nlme_f_sfo_sfo_ff(name, time, parent_0, log_k_parent, log_k_A1, f_parent_ilr_1), data = grouped_data_2, fixed = parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1, random = pdDiag(parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1), - start = mean_dp_sfo_sfo_ff)
#> Error in nlme_f_sfo_sfo_ff(name, time, parent_0, log_k_parent, log_k_A1, f_parent_ilr_1): konnte Funktion "nlme_f_sfo_sfo_ff" nicht finden
- # It does converge with this version of reduced random effects - f_nlme_sfo_sfo_ff <- nlme(value ~ nlme_f_sfo_sfo_ff(name, time, - parent_0, log_k_parent, log_k_A1, f_parent_ilr_1), - data = grouped_data_2, - fixed = parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1, - random = pdDiag(parent_0 + log_k_parent ~ 1), - start = mean_dp_sfo_sfo_ff)
#> Error in nlme_f_sfo_sfo_ff(name, time, parent_0, log_k_parent, log_k_A1, f_parent_ilr_1): konnte Funktion "nlme_f_sfo_sfo_ff" nicht finden
+ start = mean_dp_sfo_sfo_ff)
#> Error in nlme.formula(value ~ nlme_f_sfo_sfo_ff(name, time, parent_0, log_k_parent, log_k_A1, f_parent_ilr_1), data = grouped_data_2, fixed = parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1, random = pdDiag(parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1), start = mean_dp_sfo_sfo_ff): step halving factor reduced below minimum in PNLS step
f_nlme_fomc_sfo <- nlme(value ~ nlme_f_fomc_sfo(name, time, parent_0, log_alpha, log_beta, log_k_A1, f_parent_ilr_1), data = grouped_data_2, fixed = parent_0 + log_alpha + log_beta + log_k_A1 + f_parent_ilr_1 ~ 1, random = pdDiag(parent_0 + log_alpha + log_beta + log_k_A1 + f_parent_ilr_1 ~ 1), - start = mean_dp_fomc_sfo)
#> Error in nlme_f_fomc_sfo(name, time, parent_0, log_alpha, log_beta, log_k_A1, f_parent_ilr_1): konnte Funktion "nlme_f_fomc_sfo" nicht finden
+ start = mean_dp_fomc_sfo) + # DFOP-SFO and SFORB-SFO did not converge with full random effects - anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo)
#> Error in anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo): Objekt 'f_nlme_fomc_sfo' nicht gefunden
# } + anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo)
#> Model df AIC BIC logLik Test L.Ratio p-value +#> f_nlme_fomc_sfo 1 11 932.5817 967.0755 -455.2909 +#> f_nlme_sfo_sfo 2 9 1089.2492 1117.4714 -535.6246 1 vs 2 160.6675 <.0001
# }