pr_fitter_splitmat: Use predictive recursion to obtain a semiparametric estimate...
In spencerwoody/saFAB: Selection-adjusted FAB inference
Description
Usage
Arguments
Value
View source: R/pr_fitter_split.R
View source: R/rrdecon_fit_split.R
Description
Use predictive recursion to obtain a semiparametric estimate of
marginal of y,
Use predictive recursion to obtain a semiparametric estimate of
marginal of y,
Usage
1
2
3
4
5
pr_fitter_splitmat(y, mu0 = NULL, sig0 = NULL,
nulltype = "theoretical")
pr_fitter_splitmat(y, mu0 = NULL, sig0 = NULL,
nulltype = "theoretical")
Arguments
y
sample
mu0
foobar
sig0
foobar
nulltype
foobar
y
sample
mu0
foobar
sig0
foobar
nulltype
foobar
Value
a list, where my_fit is the fitted marginal or y
a list, where my_fit is the fitted marginal or y
spencerwoody/saFAB documentation built on Feb. 18, 2020, 5:56 a.m.
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Description Usage Arguments Value
View source: R/pr_fitter_split.R View source: R/rrdecon_fit_split.R
Description
Use predictive recursion to obtain a semiparametric estimate of marginal of y,
Use predictive recursion to obtain a semiparametric estimate of marginal of y,
Usage
1 2 3 4 5 | pr_fitter_splitmat(y, mu0 = NULL, sig0 = NULL,
nulltype = "theoretical")
pr_fitter_splitmat(y, mu0 = NULL, sig0 = NULL,
nulltype = "theoretical")
|
Arguments
y |
sample |
mu0 |
foobar |
sig0 |
foobar |
nulltype |
foobar |
y |
sample |
mu0 |
foobar |
sig0 |
foobar |
nulltype |
foobar |
Value
a list, where my_fit is the fitted marginal or y
a list, where my_fit is the fitted marginal or y
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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