final packaging for ape 2.5!

[ape.git] / man / CADM.global.Rd

diff --git a/man/CADM.global.Rd b/man/CADM.global.Rd
index efd57297b5c5a5983c4d3b91262497542d470f24..b6ebddc064844303d5cb0ba2e3970d73cf7572ca 100644 (file)
--- a/man/CADM.global.Rd
+++ b/man/CADM.global.Rd
@@ -1,4 +1,5 @@
 \name{CADM.global}
+\alias{CADM}
 \alias{CADM.global}
 \alias{CADM.post}
 \title{ Congruence among distance matrices }
@@ -10,8 +11,10 @@ Function \code{\link{CADM.post}} carries out a posteriori permutation tests of t
 Use in phylogenetic analysis: to identify congruence among distance matrices (D) representing different genes or different types of data. Congruent D matrices correspond to data tables that can be used together in a combined phylogenetic or other type of multivariate analysis.
 }
 \usage{
-CADM.global(Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL, silent=FALSE)
-CADM.post  (Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL, mult="holm", mantel=FALSE, silent=FALSE)
+CADM.global(Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL,
+            silent=FALSE)
+CADM.post  (Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL,
+             mult="holm", mantel=FALSE, silent=FALSE)
 }
 
 \arguments{
@@ -34,23 +37,23 @@ The corrections used for multiple testing are applied to the list of P-values (P
 
 The Holm correction is computed after ordering the P-values in a list with the smallest value to the left. Compute adjusted P-values as:
 
-\eqn{P_corr = (k-i+1)*P}
+\deqn{P_{corr} = (k-i+1)*P}{P_corr = (k-i+1)*P}
 
-where i is the position in the ordered list. Final step: from left to right, if an adjusted P_corr in the ordered list is smaller than the one occurring at its left, make the smallest one equal to the largest one.
+where i is the position in the ordered list. Final step: from left to right, if an adjusted \eqn{P_{corr}}{P_corr} in the ordered list is smaller than the one occurring at its left, make the smallest one equal to the largest one.
 
 The Sidak correction is:
 
-\eqn{P_corr = 1 - (1 - P)^k}
+\deqn{P_{corr} = 1 - (1 - P)^k}{P_corr = 1 - (1 - P)^k}
 
 The Bonferonni correction is:
 
-\eqn{P_corr = k*P}
+\deqn{P_{corr} = k*P}{P_corr = k*P}
 }
 
 \value{
 
-\code{CADM.global} produces a small table containing the W, Chi2, and Prob.perm statistics described in the following list. 
-\code{CADM.post} produces a table stored in element $A_posteriori_tests, containing Mantel.mean, Prob, and Corrected.prob statistics in rows; the columns correspond to the k distance matrices under study, labeled Dmat.1 to Dmat.k.
+\code{CADM.global} produces a small table containing the W, Chi2, and Prob.perm statistics described in the following list.
+\code{CADM.post} produces a table stored in element \code{A_posteriori_tests}, containing Mantel.mean, Prob, and Corrected.prob statistics in rows; the columns correspond to the k distance matrices under study, labeled Dmat.1 to Dmat.k.
 If parameter \code{mantel} is TRUE, tables of Mantel statistics and P-values are computed among the matrices.
 
   \item{W }{Kendall's coefficient of concordance, W (Kendall and Babington Smith 1939). }
@@ -84,7 +87,7 @@ Legendre, P. et F.-J. Lapointe. 2005. Congruence entre matrices de distance. P.
 
 Siegel, S. and N. J. Castellan, Jr. 1988. Nonparametric statistics for the behavioral sciences. 2nd edition. McGraw-Hill, New York.
 }
-\seealso{ \code{\link{kendall.W}}, \code{\link[ape:ape-package]{ape}} }
+
 \author{ Pierre Legendre, Universite de Montreal }
 
 \examples{