From ce73c044b949154e3bc3e715b9b79e1360b3f794 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 1 Nov 2019 15:34:28 +0100 Subject: Make the 'quadratic' the default for 'confint' Also the documentation was improved here and there --- docs/reference/AIC.mmkin.html | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) (limited to 'docs/reference/AIC.mmkin.html') diff --git a/docs/reference/AIC.mmkin.html b/docs/reference/AIC.mmkin.html index 7ca12302..6b782456 100644 --- a/docs/reference/AIC.mmkin.html +++ b/docs/reference/AIC.mmkin.html @@ -70,7 +70,7 @@ same dataset." /> mkin - 0.9.49.7 + 0.9.49.8 @@ -173,7 +173,10 @@ column.

f <- mmkin(c("SFO", "FOMC", "DFOP"), list("FOCUS A" = FOCUS_2006_A, "FOCUS C" = FOCUS_2006_C), cores = 1, quiet = TRUE)
#> Warning: Optimisation did not converge: -#> false convergence (8)
AIC(f[1, "FOCUS A"]) # We get a single number for a single fit
#> [1] 55.28197
+#> false convergence (8)
# We get a warning because the FOMC model does not converge for the + # FOCUS A dataset, as it is well described by SFO + + AIC(f["SFO", "FOCUS A"]) # We get a single number for a single fit
#> [1] 55.28197
AIC(f[["SFO", "FOCUS A"]]) # or when extracting an mkinfit object
#> [1] 55.28197
# For FOCUS A, the models fit almost equally well, so the higher the number # of parameters, the higher (worse) the AIC AIC(f[, "FOCUS A"])
#> df AIC @@ -182,12 +185,18 @@ column.

#> DFOP 5 59.28197
AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
#> df AIC #> SFO 3 49.28197 #> FOMC 4 49.28202 -#> DFOP 5 49.28197
+#> DFOP 5 49.28197
BIC(f[, "FOCUS A"]) # Comparing the BIC gives a very similar picture
#> df BIC +#> SFO 3 55.52030 +#> FOMC 4 57.59979 +#> DFOP 5 59.67918
# For FOCUS C, the more complex models fit better AIC(f[, "FOCUS C"])
#> df AIC #> SFO 3 59.29336 #> FOMC 4 44.68652 -#> DFOP 5 29.02372
+#> DFOP 5 29.02372
BIC(f[, "FOCUS C"])
#> df BIC +#> SFO 3 59.88504 +#> FOMC 4 45.47542 +#> DFOP 5 30.00984
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