Method to get the names of ill-defined parameters

From 9ee3d9f025ec7f5effddb0bcf9cf6e054c99794b Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 10 Aug 2022 13:21:34 +0200 Subject: Update static docs --- docs/reference/illparms.html | 48 ++++++++++++++++++++++++++++++++++++++------ 1 file changed, 42 insertions(+), 6 deletions(-) (limited to 'docs/reference/illparms.html') diff --git a/docs/reference/illparms.html b/docs/reference/illparms.html index 037d7a8c..cbdbfde2 100644 --- a/docs/reference/illparms.html +++ b/docs/reference/illparms.html @@ -1,5 +1,9 @@ -Method to get the names of ill-defined parameters — illparms • mkinMethod to get the names of ill-defined parameters — illparms • mkin @@ -83,7 +87,11 @@

The method for generalised nonlinear regression fits as obtained +with mkinfit and mmkin checks if the degradation parameters +pass the Wald test (in degradation kinetics often simply called t-test) for +significant difference from zero. For this test, the parameterisation +without parameter transformations is used.

@@ -96,6 +104,15 @@ illparms(object, conf.level = 0.95, ...) # S3 method for illparms.mmkin +print(x, ...) + +# S3 method for saem.mmkin +illparms(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...) + +# S3 method for mhmkin +illparms(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...) + +# S3 method for illparms.mhmkin print(x, ...)

@@ -116,14 +133,33 @@

The object to be printed

+ +

random

For hierarchical fits, should random effects be tested?

+ + +

errmod

For hierarchical fits, should error model parameters be +tested?

Value

For mkinfit objects, a character vector of parameter names -For mmkin objects, an object of class 'illparms.mmkin' with a -suitable printing method.

For mkinfit or saem objects, a character vector of parameter +names. For mmkin or mhmkin objects, a matrix like object of class +'illparms.mmkin' or 'illparms.mhmkin'. The latter objects have a suitable +printing method.

Details

The method for hierarchical model fits, also known as nonlinear +mixed-effects model fits as obtained with saem and mhmkin +checks if any of the confidence intervals for the random +effects expressed as standard deviations include zero, and if +the confidence intervals for the error model parameters include +zero.

@@ -157,7 +193,7 @@ suitable printing method.

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