Computes the sine expansion terms that modify the
shape of distance likelihood functions.
Usage
sine.expansion(x, expansions)
Value
A 3D array of size nrow(x) X ncol(x) X expansions.
The 'pages' (3rd dimension) of this array are the cosine expansions of
x. i.e., page 1 is the first expansion term of x,
page 2 is the second expansion term of x, etc.
Arguments
x
A numeric matrix of distances at which to evaluate
the expansion series. For distance analysis, x should
be the proportion of the maximum sighting distance
at which a group was sighted, i.e., \(x = d/w\), where \(d\)
is sighting distance and \(w\) is maximum sighting distance.
expansions
A scalar specifying the number of
expansion terms to compute. Must be one of the
integers 1, 2, 3, 4, or 5.
Details
The sine expansion used here is:
First term: $$h_1(x)=\sin(2\pi x)/2,$$
Second term: $$h_2(x)=\sin(3\pi x)/2,$$
Third term: $$h_3(x)=\sin(4\pi x)/2,$$
Fourth term: $$h_4(x)=\sin(5\pi x)/2,$$
Fifth term: $$h_5(x)=\sin(6\pi x)/2,$$
The maximum number of expansion terms is 5.
The sine expansion frequency in Rdistance is pi. Each term is one pi more than
the previous. The cosine expansion frequency in Rdistance is 2*pi. Consequently,
the sine and cosine expansions fit different models.