Bisect: An implementation of the bisection algorithm for root...
In Icens: NPMLE for Censored and Truncated Data
Description
Usage
Arguments
Details
Value
Author(s)
References
Description
Most of the optimizations in Icens have a one dimensional
root-finding component. Since the quantities involved are generally
restricted to a subset of [0,1] we use bisection to find the roots.
Usage
1
Arguments
tA
The transpose of the clique matrix.
pvec
The current estimate of the probability vector.
ndir
The direction to explore.
Meps
Machine epsilon, elements of pvec that are less
than this are assumed to be zero.
tolbis
The tolerance used to determine if the algorithm has
converged.
Details
We search from pvec in the direction ndir to obtain the
new value of pvec that maximizes the likelihood.
Value
The new estimate of pvec.
Author(s)
Alain Vandal and Robert Gentleman.
References
Any book on optimization.
Icens documentation built on Nov. 8, 2020, 8:12 p.m.
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Description Usage Arguments Details Value Author(s) References
Description
Most of the optimizations in Icens have a one dimensional root-finding component. Since the quantities involved are generally restricted to a subset of [0,1] we use bisection to find the roots.
Usage
1 |
Arguments
tA |
The transpose of the clique matrix. |
pvec |
The current estimate of the probability vector. |
ndir |
The direction to explore. |
Meps |
Machine epsilon, elements of |
tolbis |
The tolerance used to determine if the algorithm has converged. |
Details
We search from pvec in the direction ndir to obtain the
new value of pvec that maximizes the likelihood.
Value
The new estimate of pvec.
Author(s)
Alain Vandal and Robert Gentleman.
References
Any book on optimization.
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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