sparsemse: Fit the SparseMSE model
In OlivierBinette/MSETools: Interface to Multiple Systems Estimation Software
sparsemse R Documentation
Fit the SparseMSE model
Description
Fit the SparseMSE approach of Chan et al. (2020). Note: computationally-intensive bootstrap confidence intervals are only computed as part of a call to the estimates() function.
Usage
sparsemse(data, pthresh=0.02)
Arguments
data
object of class "MSEdata" representing list inclusion pattern counts.
pthresh
p-value threshold for forward stepwise p-value thresholding. Default is 0.02.
Value
Object of class "sparsemse" containing the fitted model "fit" as well as the arguments "args" passed to this function. Use the function estimates() to recover point and interval estimates.
Examples
sparsemse_fit <- sparsemse(UK)
estimates(sparsemse_fit, mc.cores = 1)
OlivierBinette/MSETools documentation built on Aug. 7, 2022, 8:42 p.m.
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| sparsemse | R Documentation |
Fit the SparseMSE model
Description
Fit the SparseMSE approach of Chan et al. (2020). Note: computationally-intensive bootstrap confidence intervals are only computed as part of a call to the estimates() function.
Usage
sparsemse(data, pthresh=0.02)
Arguments
data |
object of class "MSEdata" representing list inclusion pattern counts. |
pthresh |
p-value threshold for forward stepwise p-value thresholding. Default is 0.02. |
Value
Object of class "sparsemse" containing the fitted model "fit" as well as the arguments "args" passed to this function. Use the function estimates() to recover point and interval estimates.
Examples
sparsemse_fit <- sparsemse(UK) estimates(sparsemse_fit, mc.cores = 1)
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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