Grid of tree shapes

Crosses levels of the gamma statistic with levels of the normalized Colless index and finds the beta and c that give each combination on average, as a design for simulation studies. The levels can be chosen, for instance, from quantiles of tree_shape() over empirical trees of similar size.

Usage

shape_grid(n, gamma, colless, calibration = NULL, reps = 200)

Arguments

n

Number of tips, a single integer of at least 2.

gamma, colless

Levels of each statistic.

calibration

Output of calibrate_shape() for the same n; if NULL, it is computed with reps draws per value.

reps

Passed to calibrate_shape() when calibration is NULL.

Value

A data frame with one row per combination of levels (gamma, colless, beta, c), with the calibration in attribute calibration. Each row can be passed to sim_tree_target() (targets) or to sim_tree_shape() (parameters).

Examples

set.seed(1)
grid <- shape_grid(50, gamma = c(-2, -1, 0), colless = c(0, 0.5, 1), reps = 50)
grid
#>   gamma colless        beta           c
#> 1    -2     0.0  0.07990851 -0.50284776
#> 2    -1     0.0  0.07990851 -0.22999948
#> 3     0     0.0  0.07990851  0.02818277
#> 4    -2     0.5 -0.40207838 -0.50284776
#> 5    -1     0.5 -0.40207838 -0.22999948
#> 6     0     0.5 -0.40207838  0.02818277
#> 7    -2     1.0 -0.67972320 -0.50284776
#> 8    -1     1.0 -0.67972320 -0.22999948
#> 9     0     1.0 -0.67972320  0.02818277