hansen.fit {ouch} | R Documentation |
These functions relate to the Hansen model for phylogenetic evolution.
hansen.fit(data, node, ancestor, times, regimes = NULL, interval = c(0, 100), tol = 1e-12) hansen.prof(alpha, data, node, ancestor, times, regimes = NULL) hansen.dev(n = 1, node, ancestor, times, regimes = NULL, alpha, sigma, theta)
data |
Phenotypic data for extant species, i.e., at the terminal ends of the phylogenetic tree. |
node |
Character vector of names of the nodes. |
ancestor |
Specification of the topology of the phylogenetic tree. This is in the form of a character vector of node names, one for each node in the tree. The i-th name is that of the ancestor of the i-th node. The root node is distinguished by having no ancestor (i.e., NA). |
times |
A vector of nonnegative numbers, one per node in the tree, specifying the time at which each node is located. The root node should be assigned time 0. |
regimes |
A vector of codes, one for each node in the tree, specifying the selective regimes hypothesized to have been operative. Corresponding to each node, enter the code of the regime hypothesized for the branch segment terminating in that node. For the root node, because it has no branch segment terminating on it, the regime specification is irrelevant. |
interval |
The interval which will be searched for the optimal α. By default, 0.001 < α < 20. |
tol |
Convergence tolerance. |
n |
Number of pseudorandom data sets to generate. |
alpha |
Value of α to use. |
sigma |
Value of σ to use. |
theta |
Value of theta to use. |
The vector regimes
should be of class factor. If
regimes
is unspecified or NULL, all lineages are assumed to be
evolving under a single, global OU process with a global optimum.
In this case, rather than estimate the character state at the root
node, the algorithm assumes that the character state at the root value
follows the stationary distribution for the OU process. In general,
it is impossible to identify both the root character state and the
global optimum using contemporaneous data.
hansen.fit
returns a list containing the following elements:
alpha |
Maximum likelihood estimate of α. Note that
if α lies against one of the constraints (see
interval above), then this is not a maximum-likelihood
estimate. |
sigma |
Maximum likelihood estimate of σ. |
theta |
Maximum likelihood estimate of theta. |
loglik |
Log likelihood. |
deviance |
-2 loglik. |
aic |
Akaike information criterion. |
sic |
Schwartz information criterion (=BIC) |
df |
Number of parameters estimated (= 3 + number of regimes). |
alpha |
the specified alpha |
loglik |
the log likelihood |
deviance |
the deviance (-2 log L) |
aic |
the Akaike information criterion value |
sic |
the Schwartz information criterion value |
Note that when α=0 exactly, the computed log likelihood
does not agree with the Brownian motion model.
hansen.dev
returns a list of n
simulated data sets.
Each data set corresponds exactly to the data used in the call to
hansen.fit
.
Aaron A. King <kingaa at umich dot edu>
Butler, M.A. and A.A. King (2004) Phylogenetic comparative analysis: a modeling approach for adaptive evolution. American Naturalist 164:683-695, 2004.