| parms | R Documentation | 
This function returns degradation model parameters as well as error model parameters per default, in order to avoid working with a fitted model without considering the error structure that was assumed for the fit.
parms(object, ...)
## S3 method for class 'mkinfit'
parms(object, transformed = FALSE, errparms = TRUE, ...)
## S3 method for class 'mmkin'
parms(object, transformed = FALSE, errparms = TRUE, ...)
## S3 method for class 'multistart'
parms(object, exclude_failed = TRUE, ...)
## S3 method for class 'saem.mmkin'
parms(object, ci = FALSE, covariates = NULL, ...)
| object | A fitted model object. | 
| ... | Not used | 
| transformed | Should the parameters be returned as used internally during the optimisation? | 
| errparms | Should the error model parameters be returned in addition to the degradation parameters? | 
| exclude_failed | For multistart objects, should rows for failed fits be removed from the returned parameter matrix? | 
| ci | Should a matrix with estimates and confidence interval boundaries be returned? If FALSE (default), a vector of estimates is returned if no covariates are given, otherwise a matrix of estimates is returned, with each column corresponding to a row of the data frame holding the covariates | 
| covariates | A data frame holding covariate values for which to return parameter values. Only has an effect if 'ci' is FALSE. | 
Depending on the object, a numeric vector of fitted model parameters, a matrix (e.g. for mmkin row objects), or a list of matrices (e.g. for mmkin objects with more than one row).
saem, multistart
# mkinfit objects
fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
parms(fit)
parms(fit, transformed = TRUE)
# mmkin objects
ds <- lapply(experimental_data_for_UBA_2019[6:10],
 function(x) subset(x$data[c("name", "time", "value")]))
names(ds) <- paste("Dataset", 6:10)
## Not run: 
fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1)
parms(fits["SFO", ])
parms(fits[, 2])
parms(fits)
parms(fits, transformed = TRUE)
## End(Not run)
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