From 1ef7008be2a72a0847064ad9c2ddcfa16b055482 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 3 May 2019 19:14:15 +0200 Subject: Improve error model fitting Now we have a three stage fitting process for nonconstant error models: - Unweighted least squares - Only optimize the error model - Optimize both Static documentation rebuilt by pkgdown --- docs/reference/logLik.mkinfit.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'docs/reference/logLik.mkinfit.html') diff --git a/docs/reference/logLik.mkinfit.html b/docs/reference/logLik.mkinfit.html index 0184d573..f5844a8e 100644 --- a/docs/reference/logLik.mkinfit.html +++ b/docs/reference/logLik.mkinfit.html @@ -180,7 +180,7 @@ The total number of estimated parameters returned with the value f_nw <- mkinfit(sfo_sfo, d_t, quiet = TRUE) # no weighting (weights are unity)
#> Warning: Observations with value of zero were removed from the data
f_obs <- mkinfit(sfo_sfo, d_t, error_model = "obs", quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
f_tc <- mkinfit(sfo_sfo, d_t, error_model = "tc", quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
AIC(f_nw, f_obs, f_tc)
#> df AIC #> f_nw 5 204.4486 #> f_obs 6 205.8727 -#> f_tc 6 141.9656
+#> f_tc 6 148.1802