The model fitting of annotated phylogenetic trees can be done using either MLE via aphylo_mle() or MCMC via aphylo_mcmc(). This section describes the object of class aphylo_estimates that these functions generate and the post estimation methods/functions that can be used.

# S3 method for aphylo_estimates
print(x, ...)

# S3 method for aphylo_estimates
coef(object, ...)

# S3 method for aphylo_estimates
vcov(object, ...)

# S3 method for aphylo_estimates
plot(
  x,
  y = NULL,
  which.tree = 1L,
  ids = list(1:Ntip(x)[which.tree]),
  loo = TRUE,
  nsamples = 1L,
  ncores = 1L,
  centiles = c(0.025, 0.5, 0.975),
  cl = NULL,
  ...
)

Arguments

x, object

Depending of the method, an object of class aphylo_estimates.

...

Further arguments passed to the corresponding method.

y

Ignored.

which.tree

Integer scalar. Which tree to plot.

ids, nsamples, ncores, centiles, cl

passed to predict.aphylo_estimates()

loo

Logical scalar. When loo = TRUE, predictions are preformed similar to what a leave-one-out cross-validation scheme would be done (see predict.aphylo_estimates).

Value

Objects of class aphylo_estimates are a list withh the following elements:

par

A numeric vector of length 5 with the solution.

hist

A numeric matrix of size counts*5 with the solution path (length 2 if used optim as the intermediate steps are not available to the user). In the case of aphylo_mcmc, hist is an object of class coda::mcmc.list().

ll

A numeric scalar with the value of fun(par, dat). The value of the log likelihood.

counts

Integer scalar number of steps/batch performed.

convergence

Integer scalar. Equal to 0 if optim converged. See optim.

message

Character scalar. See optim.

fun

A function (the objective function).

priors

If specified, the function priors passed to the method.

dat

The data dat provided to the function.

par0

A numeric vector of length 5 with the initial parameters.

method

Character scalar with the name of the method used.

varcovar

A matrix of size 5*5. The estimated covariance matrix.

The plot method for aphylo_estimates returns the selected tree (which.tree) with predicted annotations, also of class aphylo.

Details

The plot method for the object of class aphylo_estimates plots the original tree with the predicted annotations.

Examples

set.seed(7881)
atree <- raphylo(40, P = 2)
res   <- aphylo_mcmc(atree ~ mu_d + mu_s + Pi)
#> Warning: While using multiple chains, a single initial point has been passed via `initial`: c(0.9, 0.5, 0.1, 0.05, 0.5). The values will be recycled. Ideally you would want to start each chain from different locations.
#> Convergence has been reached with 10000 steps. Gelman-Rubin's R: 1.0113. (500 final count of samples).

print(res)
#> 
#> ESTIMATION OF ANNOTATED PHYLOGENETIC TREE
#> 
#>  Call: aphylo_mcmc(model = atree ~ mu_d + mu_s + Pi)
#>  LogLik: -37.8064 
#>  Method used: mcmc (10000 steps)
#>  # of Leafs: 40
#>  # of Functions 2
#>  # of Trees: 1
#> 
#>          Estimate  Std. Err.
#>  mu_d0   0.8301    0.1659
#>  mu_d1   0.5980    0.1568
#>  mu_s0   0.1528    0.0715
#>  mu_s1   0.0528    0.0289
#>  Pi      0.5081    0.3012
#> 
coef(res)
#>      mu_d0      mu_d1      mu_s0      mu_s1         Pi 
#> 0.83010554 0.59795454 0.15277178 0.05277311 0.50811059 
vcov(res)
#>               mu_d0         mu_d1         mu_s0         mu_s1            Pi
#> mu_d0  0.0275156151  0.0093328072 -0.0024645276 -0.0001701106  0.0005836410
#> mu_d1  0.0093328072  0.0245869092  0.0026286693 -0.0007765479 -0.0030666673
#> mu_s0 -0.0024645276  0.0026286693  0.0051186427 -0.0002880911  0.0033794154
#> mu_s1 -0.0001701106 -0.0007765479 -0.0002880911  0.0008377113 -0.0003115157
#> Pi     0.0005836410 -0.0030666673  0.0033794154 -0.0003115157  0.0907507309
plot(res)