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author | Johannes Ranke <jranke@uni-bremen.de> | 2018-11-26 09:32:07 +0100 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2018-11-26 09:32:07 +0100 |
commit | 62e66eb483aef4edcfd839e475354ef1ddb9e49f (patch) | |
tree | 54d380b8a971eeea546520b7d8af641d17906a14 /man | |
parent | 3621588c04cbaa393ba62c97137f6aec746d114f (diff) |
Static documentation rebuilt by pkgdown
Diffstat (limited to 'man')
-rw-r--r-- | man/logLik.mkinfit.Rd | 20 |
1 files changed, 19 insertions, 1 deletions
diff --git a/man/logLik.mkinfit.Rd b/man/logLik.mkinfit.Rd index 2f911d5b..78c4e4c2 100644 --- a/man/logLik.mkinfit.Rd +++ b/man/logLik.mkinfit.Rd @@ -5,7 +5,25 @@ } \description{ This function simply calculates the product of the likelihood densities - calc + calculated using \code{\link{dnorm}}, i.e. assuming normal distribution. + + The total number of estimated parameters returned with the value + of the likelihood is calculated as the sum of fitted degradation + model parameters and the fitted error model parameters. + + For the case of unweighted least squares fitting, we calculate one + constant standard deviation from the residuals using \code{\link{sd}} + and add one to the number of fitted degradation model parameters. + + For the case of manual weighting, we use the weight given for each + observation as standard deviation in calculating its likelihood. + + In the case of iterative reweighting, the variances obtained by this + procedure are used in the likelihood calculations, and the number of + estimated parameters is obtained by the number of degradation model + parameters plus the number of variance model parameters, i.e. the number of + observed variables if the reweighting method is "obs", and two if the + reweighting method is "tc". } \usage{ \method{logLik}{mkinfit}(object, ...) |