get_estimated_pi: Return the estimated mixture proportions. Use...
In Alice-MacQueen/CDBNgenomics: Genomics Using the Cooperative Dry Bean Nursery Dataset
Description
Usage
Arguments
Details
Value
View source: R/handle_mash_results.R
Description
Return the estimated mixture proportions. Use get_estimated_pi to
extract the estimates of the mixture proportions for different types of
covariance matrix. This tells you which covariance matrices have most of
the mass.
Usage
1
get_estimated_pi(m, dimension = c("cov", "grid", "all"))
Arguments
m
the mash result
dimension
indicates whether you want the mixture proportions for the
covariances, grid, or all
Details
If the fit was done with 'usepointmass=TRUE' then the first
element of the returned vector will correspond to the null, and the
remaining elements to the non-null covariance matrices. Suppose the fit
was done with $K$ covariances and a grid of length $L$. If
'dimension=cov' then the returned vector will be of length $K$
(or $K+1$ if 'usepointmass=TRUE'). If 'dimension=grid' then
the returned vector will be of length $L$ (or $L+1$). If
'dimension=all' then the returned vector will be of length $LK$ (or
$LK+1$). The names of the vector will be informative for which
combination each element corresponds to.
Value
a named vector containing the estimated mixture proportions.
Alice-MacQueen/CDBNgenomics documentation built on Aug. 18, 2020, 4:39 p.m.
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Description Usage Arguments Details Value
View source: R/handle_mash_results.R
Description
Return the estimated mixture proportions. Use get_estimated_pi to extract the estimates of the mixture proportions for different types of covariance matrix. This tells you which covariance matrices have most of the mass.
Usage
1 | get_estimated_pi(m, dimension = c("cov", "grid", "all"))
|
Arguments
m |
the mash result |
dimension |
indicates whether you want the mixture proportions for the covariances, grid, or all |
Details
If the fit was done with 'usepointmass=TRUE' then the first element of the returned vector will correspond to the null, and the remaining elements to the non-null covariance matrices. Suppose the fit was done with $K$ covariances and a grid of length $L$. If 'dimension=cov' then the returned vector will be of length $K$ (or $K+1$ if 'usepointmass=TRUE'). If 'dimension=grid' then the returned vector will be of length $L$ (or $L+1$). If 'dimension=all' then the returned vector will be of length $LK$ (or $LK+1$). The names of the vector will be informative for which combination each element corresponds to.
Value
a named vector containing the estimated mixture proportions.
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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