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siplab (version 1.0)

influence: Influence Functions

Description

Compute influence values depending on distance and plant marks, for use in assimilation.

Usage

zoi.inf(dx, dy, marks, par = list(k = 0.2, smark = 1))

tass.inf(dx, dy, marks, par = list(b = 3.52 * 0.975, c = 6.1, smark = 1))

gates.inf(dx, dy, marks, par = list(a = 1, b = 4, smark = 1))

gnomon.inf(dx, dy, marks, par = list(a = 1, b = 4, smark = 1))

Arguments

dx
Vector of x-distances. Points x-coordinates minus plant x-coordinate.
dy
Vector of y-distances. Points y-coordinates minus plant y-coordinate.
marks
Plant mark information.
par
List of parameters.

Value

  • Vector of influence values, of length equal to the length of dx and dy.

encoding

UTF-8

Details

The values of par must be given in the argument infpar of assimilation, they are shown here as examples.

smark in par indicates the location of the plant size variable in marks. It can be a data frame column number, or a string id like "height".

Let $S$ be the plant size, and $R$ be the Euclidean plant-to-point distance $R = \sqrt{\mathrm{dx}^2 + \mathrm{dy}^2}$. Then the influence functions are: [object Object],[object Object],[object Object],[object Object]

References

http://forestgrowth.unbc.ca/siplab

García{Garcia}, O. A generic approach to spatial individual-based modelling and simulation of plant communities. Manuscript in review.

See Also

assimilation