cosine.expansion: calculation of cosine expansion for detection function likelihoods
Description
Computes the cosine expansion terms used in the likelihood of a distance analysis.
More generally, will compute a cosine expansion of any numeric vector.
Usage
cosine.expansion(x, expansions)
Value
A matrix of size length(x) X expansions. The columns of this matrix are the cosine expansions of
x. Column 1 is the first expansion term of x, column 2 is the second expansion term of x, and so on
up to expansions.
Arguments
x
In a distance analysis, x is a numeric vector of the proportion of a strip transect's half-width
at which a group of individuals were sighted. If \(w\) is the strip transect half-width or maximum sighting
distance, and \(d\) is the perpendicular off-transect distance to a sighted group (\(d\leq w\)),
x is usually \(d/w\). More generally, x is a vector of numeric values
expansions
A scalar specifying the number of expansion terms to compute. Must be one of the
integers 1, 2, 3, 4, or 5.
Details
There are, in general, several expansions that can be called cosine. The cosine expansion used here is:
First term: $$h_1(x)=\cos(2\pi x),$$
Second term: $$h_2(x)=\cos(3\pi x),$$
Third term: $$h_3(x)=\cos(4\pi x),$$
Fourth term: $$h_4(x)=\cos(5\pi x),$$
Fifth term: $$h_5(x)=\cos(6\pi x),$$
The maximum number of expansion terms computed is 5.
See Also
dfuncEstim, hermite.expansion, simple.expansion, and the discussion
of user defined likelihoods in dfuncEstim.