ndfboundp: Derivative of the bounding transformation function used by...
In colemonnahan/admbtools: Bayesian analyses using ADMB
Description
Usage
Arguments
Details
Value
Note
Author(s)
Description
Derivative of the bounding transformation function used by ADMB.
The bounding functions, with their inverses and derivatives.
Usage
1
ndfboundp(x, minb, maxb, hbf)
Arguments
x
The input value.
minb
The minimum bound.
maxb
The maximum bound.
hbf
The hybrid bounded flag. Determines which function is used.
Details
If hbf=0 then the function is minb+(maxb-minb)/(1+exp(-x)),
otherwise it is minb+(maxb-minb)*(.5*sin(x*pi/2)+.5).
Value
Numeric function value.
Note
These functions are named as in the ADMB source code.
Author(s)
Cole C. Monnahan
colemonnahan/admbtools documentation built on May 13, 2019, 8:50 p.m.
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Description Usage Arguments Details Value Note Author(s)
Description
Derivative of the bounding transformation function used by ADMB.
The bounding functions, with their inverses and derivatives.
Usage
1 | ndfboundp(x, minb, maxb, hbf)
|
Arguments
x |
The input value. |
minb |
The minimum bound. |
maxb |
The maximum bound. |
hbf |
The hybrid bounded flag. Determines which function is used. |
Details
If hbf=0 then the function is minb+(maxb-minb)/(1+exp(-x)),
otherwise it is minb+(maxb-minb)*(.5*sin(x*pi/2)+.5).
Value
Numeric function value.
Note
These functions are named as in the ADMB source code.
Author(s)
Cole C. Monnahan
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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