From 8b7edd4eaf0d196e674a085f744d1a69260a6c91 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 16 Nov 2023 06:02:05 +0100 Subject: Update pkgdown docs to bootstrap 5 with search --- docs/reference/aw.html | 192 ++++++++++++++++++++----------------------------- 1 file changed, 78 insertions(+), 114 deletions(-) (limited to 'docs/reference/aw.html') diff --git a/docs/reference/aw.html b/docs/reference/aw.html index 5740d67d..953d9e22 100644 --- a/docs/reference/aw.html +++ b/docs/reference/aw.html @@ -1,122 +1,90 @@ -Calculate Akaike weights for model averaging — aw • mkinCalculate Akaike weights for model averaging — aw • mkin + + Skip to contents -
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Calculate Akaike weights for model averaging

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Calculate Akaike weights for model averaging

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aw.Rd
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Akaike weights are calculated based on the relative expected Kullback-Leibler information as specified by Burnham and Anderson (2004).

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Usage

aw(object, ...)
 
 # S3 method for mkinfit
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 aw(object, ...)
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Arguments

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Arguments

object

An mmkin column object, containing two or more mkinfit models that have been fitted to the same data, @@ -147,15 +115,15 @@ as dots arguments.

further mkinfit objects in the method for mkinfit objects.

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References

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References

Burnham KP and Anderson DR (2004) Multimodel Inference: Understanding AIC and BIC in Model Selection. Sociological Methods & Research 33(2) 261-304

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Examples

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Examples

# \dontrun{
 f_sfo <- mkinfit("SFO", FOCUS_2006_D, quiet = TRUE)
 f_dfop <- mkinfit("DFOP", FOCUS_2006_D, quiet = TRUE)
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 # }
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