Calculated the log-likelihood of a fitted mkinfit object

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This function returns the product of the likelihood densities of each -observed value, as calculated as part of the fitting procedure using -dnorm, i.e. assuming normal distribution, and with the means -predicted by the degradation model, and the standard deviations predicted by -the error model.

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# S3 method for mkinfit
-logLik(object, ...)

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Arguments

object: An object of class mkinfit.
...: For compatibility with the generic method

Value

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An object of class logLik with the number of estimated -parameters (degradation model parameters plus variance model parameters) -as attribute.

Details

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.

Author

Johannes Ranke

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Examples


-  # \dontrun{
-  sfo_sfo <- mkinmod(
-    parent = mkinsub("SFO", to = "m1"),
-    m1 = mkinsub("SFO")
-  )
-#> Temporary DLL for differentials generated and loaded
-  d_t <- subset(FOCUS_2006_D, value != 0)
-  f_nw <- mkinfit(sfo_sfo, d_t, quiet = TRUE) # no weighting (weights are unity)
-  f_obs <- update(f_nw, error_model = "obs")
-  f_tc <- update(f_nw, error_model = "tc")
-  AIC(f_nw, f_obs, f_tc)
-#>       df      AIC
-#> f_nw   5 204.4486
-#> f_obs  6 205.8727
-#> f_tc   6 141.9656
-  # }
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