F.gx.estim {Rdistance} | R Documentation |
F.gx.estim - Estimate g(0) or g(x)
Description
Estimate g(0) or g(x) for a specified distance function.
Usage
F.gx.estim(fit, x.scl = NULL, g.x.scl = NULL, observer = NULL)
Arguments
fit |
An estimated |
x.scl |
The x coordinate (a distance) at which to scale the
sightability function to |
g.x.scl |
Height of the distance function at coordinate x.
The distance function
will be scaled so that g( |
observer |
A numeric scalar or text string specifying whether observer 1
or observer 2 or both were full-time observers.
This parameter dictates which set of observations form the denominator
of a double observer system.
If, for example, observer 2 was a data recorder and part-time observer,
or if observer 2 was the pilot, set |
Details
This routine scales sightability such that
g(x.scl
) = g.x.scl
, where g() is the sightability function.
Specification of x.scl
and g.x.scl
covers several estimation cases:
-
g(0) = 1 : (the default) Inputs are
x.scl
= 0,g.x.scl
= 1. Ifw.lo
> 0,x.scl
will be set tow.lo
so technically this case is g(w.low
) = 1. -
User supplied probability at specified distance: Inputs are
x.scl
= a number greater than or equal tow.lo
,g.x.scl
= a number between 0 and 1. This case covers situations where sightability on the transect (distance 0) is not perfect. This case assumes researchers have an independent estimate of sightability at distancex.scl
off the transect. For example, researchers could be using multiple observers to estimate that sightability at distancex.scl
isg.x.scl
. -
Maximum sightability specified: Inputs are
x.scl
="max",g.x.scl
= a number between 0 and 1. In this case, g() is scaled such that its maximum value isg.x.scl
. This routine computes the distance at which g() is maximum, sets g()'s height there tog.x.scl
, and returnsx.max
where x.max is the distance at which g is maximized. This case covers the common aerial survey situation where maximum sightability is slightly off the transect, but the distance at which the maximum occurs is unknown. This case is the default, withg.x.scl
= 1, when gamma distance functions are estimated. -
Double observer system: Inputs are
x.scl
="max",g.x.scl
= <a data frame>. In this case, g(x) = h, where x is the distance that maximizes g and h is the height of g() at x computed from the double observer data frame (see below for structure of the double observer data frame). -
Distance of independence specified, height computed from double observer system: Inputs are
x.scl
= a number greater than or equal tow.lo
g.x.scl
= a data frame. In this case, g(x.scl
) = h, where h is computed from the double observer data frame (see below for structure of the double observer data frame).
When x.scl
, g.x.scl
, or observer
are NULL, the routine
will look for and use $call.x.scl
, or $call.g.x.scl
, or
$call.observer
components of the fit
object for whichever
of these three parameters is missing. Later, different
values can be specified in a direct call to F.gx.estim
without having to re-estimate the distance function. Because of this feature,
the default values in dfuncEstim
are x.scl
= 0 and
g.x.scl
= 1 and observer
= "both".
Value
A list comprised of the following components:
x.scl |
The value of x (distance) at which g() is evaluated. |
comp2 |
The estimated value of g() when evaluated at |
Structure of the double observer data frame
When g.x.scl
is a data frame, it is assumed to contain
the components $obsby.1
and $obsby.2
(no flexibility on names).
Each row in the data frame contains data from one sighted target.
The $obsby.1
and $obsby.2
components are
TRUE/FALSE (logical) vectors indicating whether
observer 1 (obsby.1
) or observer 2 (obsby.2
) spotted the target.
See Also
Examples
set.seed(555574)
x <- rnorm(1000) * 100
x <- x[ 0 < x & x < 100 ]
x <- units::set_units(x, "m")
un.dfunc <- dfuncEstim( x ~ 1
, likelihood = "logistic")
F.gx.estim(un.dfunc)
x <- rgamma(1000, shape = 5)
x <- units::set_units(x, "m")
gam.dfunc <- dfuncEstim( x ~ 1
, likelihood="Gamma")
F.gx.estim(gam.dfunc)