View source: R/MCMCglmm.subsets.R
MCMCglmm.subsets | R Documentation |
Creating a dispRity object from a MCMCglmm posterior output
MCMCglmm.subsets(
data,
posteriors,
group,
tree,
rename.groups,
set.loc = TRUE,
...
)
data |
The |
posteriors |
A |
group |
Optional, a named vector of which group to include from the posteriors (if left empty the random and residual terms are used). See details. |
tree |
Optional, the tree(s) used in the MCMCglmm analyses. |
rename.groups |
Optional, a vector of group names for renaming them. See details. |
set.loc |
Optional, if no location is available for a subset ( |
... |
Optional arguments to be passed to |
For the group
option, the group names must be ones found in the posteriors
formula in the format <Type = Term:FactorLevel> as returned by MCMCglmm.levels(posteriors)
. For example, for returning two random effect, the phylogenetic one ("animal"
) and one for a specific clade (say the 2nd clade) as well as two residual terms for a specific factor (say level 1 and 4) you can use group = c(random = "animal", random = "animal:clade2", residual = "units:myfactor1", residual = "units:myfactor4")
.
For the rename.groups
option, the vector must be of class "character"
and must of the same length as the number of random and residual terms in posteriors
or of group
argument (if used). If the group
argument is left empty, the groups are extracted from the posteriors
in the following order: the random terms first then the residual terms as specified in the posteriors
object formulas (respectively posteriors$Random$formula
and posteriors$Residual$formula
).
NOTE that the output dispRity
inherits the dimensions used in the posteriors
argument. You can always check the selected dimensions using:
data$call$dimensions
Thomas Guillerme
dispRity
covar.plot
data(charadriiformes)
## Creating a dispRity object from the charadriiformes model
MCMCglmm.subsets(data = charadriiformes$data,
posteriors = charadriiformes$posteriors)
## Same but selecting only the three first random terms
MCMCglmm.subsets(data = charadriiformes$data,
posteriors = charadriiformes$posteriors,
tree = charadriiformes$tree,
group = MCMCglmm.levels(
charadriiformes$posteriors)[1:3],
rename.groups = c("gulls", "plovers", "sandpipers"))
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