Package: Kendall
Version: 2.2.1
Date: 2011-05-16
= TRUE,
est_type="bivariate", observations = matrix(rnorm(30*2), nrow=30,
ncol=2, byrow = TRUE))
R: Correlation of Kendall
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML
^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
R: Correlation of Kendall
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML
R: Kendalls Tau for a matrix
kendallsR Documentation
Kendalls Tau for a matrix
R: Kendall rank correlation
KendallR Documentation
Kendall rank correlation
Examples
tree <- data.frame(from = c(1, 1, 2, 2, 3, 3), to = c(2, 3, 4, 5, 6, 7))
kendall(tree)
R: Kendalls Tau for a matrix
kendallsR Documentation
Kendalls Tau for a matrix
R: Generic for Kendall correlations
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function
R: Kendall test for dependence
KendallR Documentation
Kendall test for dependence
= TRUE,
est_type="bivariate", observations = matrix(rnorm(30*2), nrow=30,
ncol=2, byrow = TRUE))
R: miRNA target prediction with the Kendall correlation...
KendallR Documentation
miRNA target prediction
R: Return a variant of the Kendall tau-a correlation for two...
kendallR Documentation
Return a variant
R: Kendall tau trend with continuity correction for time-series
const macros = { "\\R": "\\textsf{R}", "\\code
, { throwOnError: false, macros }); }
return;
KendallR Documentation
Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of
of Washington.
Usage
data("WA")
## tolerance DW
mod3 <- wa(SumSST ~ ., data = ImbrieKipp, tol.dw = TRUE,
min.tol = 2, small.tol = "mean
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