competition: Build a virtual competition model
In skayondo/breed_forest: Statistical Methods for Forest Genetic Resources Analysts

Description Usage Arguments Details Value

Given the coordinates of a set of observations, a decay parameter and a structure matrix, compute the incidence matrix of competition, and return a random effect with the given structure.

1	competition(coordinates, covariance, precision, decay, autofill = TRUE)

`coordinates`	two-column matrix-like set of row and column coordinates of observational units
`covariance`	matrix-like object
`precision`	matrix-like object
`decay`	numeric. The positive value of the decay parameter α. Typically 1 or 2. See Details.
`autofill`	logical. If TRUE (default) it will try to fill missing rows or columns with missing observations. Otherwise, will treat individuals as neighbours even if they are across an empty line.

The competition model attributes to each individual a random effect of competition with variance σ_{a_c}^2, which impacts the phenotype of the neighbours rather than its own phenotype.

Conversely, the effect of the competition over one's phenotype is given by the additive-genetic competition effects of the neighbours, weighted by the relative distances. If α is the decay parameter and a_c is the random competition effect of a neighbour at distance d, then the Weighted Neighbour Competition effect over one's phenotype is given by

∑_{neighbours} k (1/d)^α a_c,

where k is a normalizing constant which makes Var(wnc) = σ_{a_c}^2 and independent of the number of neighbours.

An object inheriting from spatial.

skayondo/breed_forest documentation built on Aug. 11, 2020, 12:35 a.m.