diff options
| -rw-r--r-- | R/logLik.mkinfit.R | 28 | ||||
| -rw-r--r-- | R/mkinfit.R | 7 |
2 files changed, 11 insertions, 24 deletions
diff --git a/R/logLik.mkinfit.R b/R/logLik.mkinfit.R index d3f4232d..d812f177 100644 --- a/R/logLik.mkinfit.R +++ b/R/logLik.mkinfit.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 @@ -16,29 +16,9 @@ # You should have received a copy of the GNU General Public License along with # this program. If not, see <http://www.gnu.org/licenses/> logLik.mkinfit <- function(object, ...) { - y_ij <- object$data$observed - yhat_ij <- object$data$predicted - if (is.null(object$data$err)) { - # For unweighted fits we estimate a single value for sigma from the residuals - err <- sd(object$data$residual) - n_var_comp <- 1 # Number of variance components estimated - } else { - err <- object$data$err - # For weighted fits we check for variance models used in IRLS - # If the variance values (err) were given and were not - # reweighted, the number of variance components estimated is zero - if (is.null(object$reweight.method)) { - n_var_comp <- 0 - } else { - n_var_comp <- switch(object$reweight.method, - obs = length(object$var_ms_unweighted), - tc = 2) - } - } - prob_dens <- dnorm(y_ij, yhat_ij, err) - val <- log(prod(prob_dens)) - class(val) <- "logLik" - attr(val, "df") <- length(coef(object)) + n_var_comp + val <- object$logLik + # Number of estimated parameters + attr(val, "df") <- length(object$bparms.optim) + length(object$errparms) return(val) } # vim: set ts=2 sw=2 expandtab: diff --git a/R/mkinfit.R b/R/mkinfit.R index 73c2f485..6c12d027 100644 --- a/R/mkinfit.R +++ b/R/mkinfit.R @@ -64,6 +64,12 @@ mkinfit <- function(mkinmod, observed, observed <- subset(observed, name %in% obs_vars)
observed <- subset(observed, !is.na(value))
+ # Also remove zero values to avoid instabilities (e.g. of the 'tc' error model)
+ if (any(observed$value == 0)) {
+ warning("Observations with value of zero were removed from the data")
+ observed <- subset(observed, value != 0)
+ }
+
# Obtain data for decline from maximum mean value if requested
if (from_max_mean) {
# This is only used for simple decline models
@@ -405,6 +411,7 @@ mkinfit <- function(mkinmod, observed, } else {
if(!quiet) cat("Optimisation successfully terminated.\n")
}
+ fit$logLik <- - nlogLik.current
# We need to return some more data for summary and plotting
fit$solution_type <- solution_type
|