From 9fc53cd2b72b2fb95a9c0b203144b9bd065bb1a3 Mon Sep 17 00:00:00 2001 From: paradis Date: Mon, 27 Jun 2011 09:18:33 +0000 Subject: [PATCH] some updates (including new CADM.global.Rd file) git-svn-id: https://svn.mpl.ird.fr/ape/dev/ape@163 6e262413-ae40-0410-9e79-b911bd7a66b7 --- NEWS | 3 ++- R/PGLS.R | 4 ++-- man/CADM.global.Rd | 28 ++++++++++++++++++++-------- 3 files changed, 24 insertions(+), 11 deletions(-) diff --git a/NEWS b/NEWS index 2a2601e..a3aa8c9 100644 --- a/NEWS +++ b/NEWS @@ -15,7 +15,8 @@ BUG FIXES o Simulation of OU process with rTraitCont() did not work correctly. This now uses formula from Gillespie (1996) reduced to a BM - process when alpha = 0 avoiding division by zero. + process when alpha = 0 to avoid division by zero. The option + 'linear' has been removed. diff --git a/R/PGLS.R b/R/PGLS.R index 510f401..6b6f4af 100644 --- a/R/PGLS.R +++ b/R/PGLS.R @@ -187,8 +187,8 @@ coef.corGrafen <- function(object, unconstrained = TRUE, ...) compute.brlen <- function(phy, method = "Grafen", power = 1, ...) { - if (!"phylo" %in% class(phy)) - stop('object "phy" is not of class "phylo"') + if (!inherits(phy, "phylo")) + stop('object "phy" is not of class "phylo"') Ntip <- length(phy$tip.label) Nnode <- phy$Nnode Nedge <- dim(phy$edge)[1] diff --git a/man/CADM.global.Rd b/man/CADM.global.Rd index b6ebddc..05bf426 100644 --- a/man/CADM.global.Rd +++ b/man/CADM.global.Rd @@ -56,7 +56,7 @@ The Bonferonni correction is: \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). } + \item{W }{Kendall's coefficient of concordance, W (Kendall and Babington Smith 1939; see also Legendre 2010). } \item{Chi2 }{Friedman's chi-square statistic (Friedman 1937) used in the permutation test of W. } \item{Prob.perm }{Permutational probability. } @@ -69,9 +69,9 @@ If parameter \code{mantel} is TRUE, tables of Mantel statistics and P-values are } \references{ -Campbell, V., P. Legendre and F.-J. Lapointe. 2009. Assessing congruence among ultrametric distance matrices. Journal of Classification (In press). +Campbell, V., P. Legendre and F.-J. Lapointe. 2009. Assessing congruence among ultrametric distance matrices. Journal of Classification 26: 103-117. -Campbell, V., P. Legendre and F.-J. Lapointe. Performance of the congruence test among distance matrices in phylogenetic analysis. (Submitted MS). +Campbell, V., P. Legendre and F.-J. Lapointe. 2011. The performance of the Congruence Among Distance Matrices (CADM) test in phylogenetic analysis. BMC Evolutionary Biology 11: 64. http://www.biomedcentral.com/1471-2148/11/64. Friedman, M. 1937. The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32: 675-701. @@ -79,7 +79,7 @@ Kendall, M. G. and B. Babington Smith. 1939. The problem of m rankings. Annals o Lapointe, F.-J., J. A. W. Kirsch and J. M. Hutcheon. 1999. Total evidence, consensus, and bat phylogeny: a distance-based approach. Molecular Phylogenetics and Evolution 11: 55-66. -Legendre, P. 2008. Coefficient of concordance. In: Encyclopedia of Research Design. SAGE Publications (in press). +Legendre, P. 2010. Coefficient of concordance. Pp. 164-169 in: Encyclopedia of Research Design, Vol. 1. N. J. Salkind, ed. SAGE Publications, Inc., Los Angeles. Legendre, P. and F.-J. Lapointe. 2004. Assessing congruence among distance matrices: single malt Scotch whiskies revisited. Australian and New Zealand Journal of Statistics 46: 615-629. @@ -97,27 +97,39 @@ Siegel, S. and N. J. Castellan, Jr. 1988. Nonparametric statistics for the behav # identical evolutionary parameters (GTR+ Gamma + I). Distance matrices were # computed from the DNA sequence matrices using a p distance corrected with the # same parameters as those used to simulate the DNA sequences. See Campbell et -# al. (submitted) for details. +# al. (2009) for details. -# First example: five independent additive trees. Data provided by V. Campbell. +# Example 1: five independent additive trees. Data provided by V. Campbell. data(mat5Mrand) res.global <- CADM.global(mat5Mrand, 5, 50) -# Second example: three partly similar trees, two independent trees. +# Example 2: three partly similar trees, two independent trees. # Data provided by V. Campbell. data(mat5M3ID) res.global <- CADM.global(mat5M3ID, 5, 50) res.post <- CADM.post(mat5M3ID, 5, 50, mantel=TRUE) -# Third example: three matrices respectively representing Serological +# Example 3: three matrices respectively representing Serological # (asymmetric), DNA hybridization (asymmetric) and Anatomical (symmetric) # distances among 9 families. Data from Lapointe et al. (1999). data(mat3) res.global <- CADM.global(mat3, 3, 9, nperm=999) res.post <- CADM.post(mat3, 3, 9, nperm=999, mantel=TRUE) + +# Example 4, showing how to bind two D matrices (cophenetic matrices +# in this example) into a file using rbind(), then run the global test. + +a <- rtree(5) +b <- rtree(5) +A <- cophenetic(a) +B <- cophenetic(b) +x <- rownames(A) +B <- B[x, x] +M <- rbind(A, B) +CADM.global(M, 2, 5) } \keyword{ multivariate } -- 2.39.2