diff options
Diffstat (limited to 'man/mkinfit.Rd')
| -rw-r--r-- | man/mkinfit.Rd | 18 |
1 files changed, 8 insertions, 10 deletions
diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd index f7dd7009..85b742e8 100644 --- a/man/mkinfit.Rd +++ b/man/mkinfit.Rd @@ -31,8 +31,8 @@ mkinfit(mkinmod, observed, quiet = FALSE, atol = 1e-8, rtol = 1e-10, n.outtimes = 100, error_model = c("const", "obs", "tc"), - error_model_algorithm = c("d_3", "direct", "twostep", "threestep", "fourstep", "IRLS", - "OLS"), + error_model_algorithm = c("auto", "d_3", "direct", "twostep", "threestep", + "fourstep", "IRLS", "OLS"), reweight.tol = 1e-8, reweight.max.iter = 10, trace_parms = FALSE, ...) } @@ -175,12 +175,13 @@ mkinfit(mkinmod, observed, distribution as assumed by this method. } \item{error_model_algorithm}{ - If the error model is "const", the error model algorithm is ignored, - because no special algorithm is needed and unweighted (also known as - ordinary) least squares fitting (listed as "OLS" in the summary) can be - applied. + If "auto", the selected algorithm depends on the error model. + If the error model is "const", nonlinear least squares fitting ("OLS") is + selected. If the error model is "obs", iteratively reweighted least squares + fitting ("IRLS") is selected. If the error model is "tc", the "d_3" + algorithm is selected. - The default algorithm "d_3" will directly minimize the negative + The algorithm "d_3" will directly minimize the negative log-likelihood and - independently - also use the three step algorithm described below. The fit with the higher likelihood is returned. @@ -206,9 +207,6 @@ mkinfit(mkinmod, observed, parameters and subsequent optimization of the degradation model using those error model parameters, until the error model parameters converge. - - The algorithm "OLS" (Ordinary Least Squares) is automatically selected when - the error model is "const" and results in an unweighted least squares fit. } \item{reweight.tol}{ Tolerance for the convergence criterion calculated from the error model |