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
of Indonesia cities and regencies with the ID.
Usage
kota
which compute Kronecker product for PIC method
Description
This is an internal function which compute Kronecker product for PIC method
a kernel projection regression. It returns a function which predicts labels for new data points.
Usage
kpr(model,
Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of
, and variable similarity kernels Q_1, ..., Q_q.
Usage
KPR(
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
Type: Package
Package: wastdr
Title: WA Sea Turtle Database 'WAStD' API Wrapper
Package: KPR
Type: Package
Title: Kernel-penalized regression
(class = `sf`)
#' @rdname wa-counties-boundaries
#' @export
-wa/etlTurtleNesting
BugReports: https://github.com/dbca-wa/etlTurtleNesting/issues
License: MIT + file LICENSE
, https://github.com/dbca-wa/rOzCBI, https://dbca-wa.github.io/rOzCBI/
BugReports: https://github.com/dbca-wa/rOzCBI
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.