negexp.like: Negative exponential likelihood

In Rdistance: Density and Abundance from Distance-Sampling Surveys

Negative exponential likelihood

Description

Computes the negative exponential distance function.

Usage

negexp.like(a, dist, covars, w.hi = NULL)

Arguments

a	A vector or matrix of covariate and expansion term coefficients. If matrix, dimension is k X p, where k = nrow(a)) is the number of coefficient vectors to evaluate (cases) and p = ncol(a)) is the number of covariate and expansion coefficients in the likelihood (i.e., rows are cases and columns are covariates). If a is a dimensionless vector, it is interpreted as a single row with k = 1. Covariate coefficients in a are the first q values (q <= p), and must be on a log scale.
dist	A numeric vector of length n or a single-column matrix (dimension nX1) containing detection distances at which to evaluate the likelihood.
covars	A numeric vector of length q or a matrix of dimension nXq containing covariate values associated with distances in argument dist.
w.hi	A numeric scalar containing maximum distance. The right-hand cutoff or upper limit. Ignored by some likelihoods (such as halfnorm, negexp, and hazrate), but is a fixed parameter in other likelihoods (such as oneStep and uniform).

Details

The negative exponential likelihood is

f(x|\alpha) = \exp(-\alpha x)

where \alpha is the slope parameter.

Value

A list containing the following two components:

• L.unscaled: A matrix of size nXk containing likelihood values evaluated at distances in dist. Each row is associated with a single distance, and each column is associated with a single case (row of a). This matrix is "unscaled" because the underlying likelihood does not integrate to one. Values in L.unscaled are always greater than or equal to zero.

• params: A nXkXb array of the likelihood's (canonical) parameters in link space (i.e., on log scale). First page contains parameter values related to covariates (i.e., s = exp(x'a)), while subsequent pages contain other parameters. b = 1 for halfnorm, negexp; b = 2 for hazrate, oneStep, Gamma, and others. Rows correspond to distances in dist. Columns correspond to rows from argument a.

See Also

dfuncEstim, abundEstim, other <likelihood>.like functions

Examples

d <- seq(0, 100, length=100)
covs <- matrix(1,length(d),1)
negexp.like(log(0.01), d, covs)

# Changing slope parameter
plot(d, negexp.like(log(0.1), d, covs)$L.unscaled, type="l", col="red")
lines(d, negexp.like(log(0.05), d, covs)$L.unscaled, col="blue")

Rdistance documentation built on Jan. 10, 2026, 1:07 a.m.