AnalyticalOptim: Optimize lambda0 and pi0, using Poisson version of analytical...
In LocFDRPois: Functions for Performing Local FDR Estimation when Null and Alternative are Poisson
Description
Optimize lambda0 and pi0, using Poisson version of analytical approach
in Efron's "Microarrays, Empirical Bayes, and the Two-Groups Model"
In the paper, he derives formulas for arbitrary support. We use support
[0, 1] for estimating the null. We initialize the search with lambda=0.05 and
pi=0.95.
Usage
1
AnalyticalOptim(r0, r1, N)
Arguments
r0
The number of 0's in the data.
r1
The number of 1's in the data.
N
The total number of points in the data.
LocFDRPois documentation built on May 2, 2019, 1:08 p.m.
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Description
Optimize lambda0 and pi0, using Poisson version of analytical approach in Efron's "Microarrays, Empirical Bayes, and the Two-Groups Model"
In the paper, he derives formulas for arbitrary support. We use support [0, 1] for estimating the null. We initialize the search with lambda=0.05 and pi=0.95.
Usage
1 | AnalyticalOptim(r0, r1, N)
|
Arguments
r0 |
The number of 0's in the data. |
r1 |
The number of 1's in the data. |
N |
The total number of points in the data. |
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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