A_star: Computes the BR adjustment
In rugbel/BRTemplate: Template for BR Estimation for Independent Data Models
Description
Usage
Arguments
Details
Value
Author(s)
References
Examples
Description
Computes the BR adjustement based on the expected Fisher information.
Usage
1
A_star(para, X, y, ncores, dll)
Arguments
para
Parameter vector.
X
Model matrix.
y
Observed response.
ncores
Number of cores used in estimation.
dll
Name of the C++ template representing the model of interest.
Details
The function can be used for both the computation of the adjustment based on the empirical
approximation to the expected values and the computation based on the Monte Carlo approximation.
In the first case, X and y would refer to observed data, while in the second
case they would refer to the simulated data. This is handled by the gsolv function.
Value
The returned value is a vector of the same size of para, containing the
value of the adjustment.
Author(s)
Ruggero Bellio
References
Kosmidis, I. and Firth, D. (2010). A generic algorithm for reducing bias
in parametric estimation. Electron. J. Statist., 4, 1097-1112.
Examples
1
# See the vignette file
rugbel/BRTemplate documentation built on Nov. 12, 2019, 7:41 a.m.
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Description Usage Arguments Details Value Author(s) References Examples
Description
Computes the BR adjustement based on the expected Fisher information.
Usage
1 | A_star(para, X, y, ncores, dll)
|
Arguments
para |
Parameter vector. |
X |
Model matrix. |
y |
Observed response. |
ncores |
Number of cores used in estimation. |
dll |
Name of the C++ template representing the model of interest. |
Details
The function can be used for both the computation of the adjustment based on the empirical
approximation to the expected values and the computation based on the Monte Carlo approximation.
In the first case, X and y would refer to observed data, while in the second
case they would refer to the simulated data. This is handled by the gsolv function.
Value
The returned value is a vector of the same size of para, containing the
value of the adjustment.
Author(s)
Ruggero Bellio
References
Kosmidis, I. and Firth, D. (2010). A generic algorithm for reducing bias in parametric estimation. Electron. J. Statist., 4, 1097-1112.
Examples
1 | # See the vignette file
|
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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