WA: Weighted averaging (WA) regression and calibration
R: Weighted averaging (WA) regression and calibration
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt
R: Weighted averaging (WA) regression and calibration
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt
R: Weighted averaging (WA) regression and calibration
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt
in Imai and Li (2019).
Usage
PAPE(T, That, Y, budget = NA, centered = TRUE)
in Imai and Li (2019).
Usage
PAPE(T, That, Y, budget = NA, centered = TRUE)
in Imai and Li (2019).
Usage
PAPE(T, That, Y, plim = NA)
Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of
of Washington.
Usage
data("WA")
and classicial
deshrinking are supported.
Usage
of Washington.
Usage
data("WA")
of Washington.
Usage
data("WA")
solution
Description
Extracts the weighted averages of a CCA solution
, i.e. a bootstrap procedure is implemented to perform the test, see crit.values.
Usage
WA(data, k_estimator)
of a CCA solution
Description
Extracts the weighted averages of a CCA solution
Package: turtleviewer
Title: WA Turtle Data Viewer
Version: 0.2.0.20200102
R: Cluster
ClusterR Documentation
Cluster
R: Clustering
clustersR Documentation
Clustering
R: Cluster
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {
R: Cluster
sg_clusterR Documentation
Cluster
R: Clustering
clusteringR Documentation
Clustering
R: *cluster*
clusterR Documentation
cluster
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