From a77a10ea6c607346778ba0700b3b66ac393101a2 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 27 May 2020 06:06:08 +0200 Subject: Create up to date pkgdown docs in development mode --- docs/dev/reference/aw.html | 221 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 221 insertions(+) create mode 100644 docs/dev/reference/aw.html (limited to 'docs/dev/reference/aw.html') diff --git a/docs/dev/reference/aw.html b/docs/dev/reference/aw.html new file mode 100644 index 00000000..267c3b0b --- /dev/null +++ b/docs/dev/reference/aw.html @@ -0,0 +1,221 @@ + + + + + + + + +Calculate Akaike weights for model averaging — aw • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+

Calculate Akaike weights for model averaging

+ Source: R/aw.R + +
+ +
+

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

+
+ + 
aw(object, ...)
+
+# S3 method for mkinfit
+aw(object, ...)
+
+# S3 method for mmkin
+aw(object, ...)
+ +

Arguments

+ + + + + + + + + + +
object

An mmkin column object, containing two or more +mkinfit models that have been fitted to the same data, +or an mkinfit object. In the latter case, further mkinfit +objects fitted to the same data should be specified +as dots arguments.

...

Not used in the method for mmkin column objects, +further mkinfit objects in the method for mkinfit objects.

+ +

References

+ +

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

+ +

Examples

+ 
# \dontrun{
+f_sfo <- mkinfit("SFO", FOCUS_2006_D, quiet = TRUE)
+f_dfop <- mkinfit("DFOP", FOCUS_2006_D, quiet = TRUE)
+aw_sfo_dfop <- aw(f_sfo, f_dfop)
+sum(aw_sfo_dfop)
#> [1] 1
aw_sfo_dfop # SFO gets more weight as it has less parameters and a similar fit
#> [1] 0.5970258 0.4029742
f <- mmkin(c("SFO", "FOMC", "DFOP"), list("FOCUS D" = FOCUS_2006_D), cores = 1, quiet = TRUE)
+aw(f)
#> [1] 0.4808722 0.1945539 0.3245740
sum(aw(f))
#> [1] 1
aw(f[c("SFO", "DFOP")])
#> [1] 0.5970258 0.4029742
# }
+
+
+ +
+ + + +
+ + + + + + + + -- cgit v1.2.1