WA: Weighted averaging (WA) regression and calibration
^2 + v2^2.
Function crossval also returns an object of class WA and adds the following named elements:
predicted
^2 + v2^2.
Function crossval also returns an object of class WA and adds the following named elements:
predicted
^2 + v2^2.
Function crossval also returns an object of class WA and adds the following named elements:
predicted
: false, macros }); }
return;
trapsR Documentation
Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of
f <- function(x) { sin(x)^2 + cos(x)^2 }
trap(f, -pi, pi, m = 10)
trap(f, -pi, pi, m = 100)
of Washington.
Usage
data("WA")
of method, only linear interpolation is used
for areas of intervals beginning or ending with y: 0.
Usage
## tolerance DW
mod3 <- wa(SumSST ~ ., data = ImbrieKipp, tol.dw = TRUE,
min.tol = 2, small.tol = "mean
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
Package: frog-trap
Type: Package
Title: Draft manuscript and code on ecological traps
Type: Package
Package: wastdr
Title: WA Sea Turtle Database 'WAStD' API Wrapper
Package: tRap
Title: A biophysical model for transcription factor binding affinities
Version: 0.7
R: compute transcription factor binding site affinity
tRap-packageR Documentation
compute transcription factor
and from air, track surveys, and camera trap surveys. Some wolves
#' may be present but are not detected.
#'
#' The TRAP method to predict transcription factor binding affinity to DNA
#' sequences (Roider et al 2007)
#'
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