bounds.plain.internal: Computes upper identification interval without shape...
In jrzubizarreta/scbounds: Shape-constrained partial identification of a population mean under unknown probabilities of sample selection

Computes upper identification interval without shape constraints, as in Aronow & Lee (2013).

1 2	bounds.plain.internal(X, sampling.ratio = 5, xmin = NULL, xmax = NULL, buckets = 1000)

`X`	The observed data.
`sampling.ratio`	Bound on the sampling weights gamma.
`xmin`	Used to construct histogram representation.
`xmax`	Used to construct histogram representation.
`buckets`	Used to construct histogram representation.

mu.bound The upper bound for mu(x).

Xhat Unweighted empirical CDF of the data.

xvals Points at which Xhat is evaluated.

Xhat.weighted Weighted version of Xhat that maximizes mu, subject to sampling ratio constraint.

jrzubizarreta/scbounds documentation built on May 20, 2019, 5:26 p.m.

jrzubizarreta/scbounds index

Note that we can't provide technical support on individual packages. You should contact the package authors for that.

Description