- CHANGES IN APE VERSION 2.5
+ CHANGES IN APE VERSION 2.5-1
+
+
+BUG FIXES
+
+ o rTraitDisc() did not use its 'freq' argument correctly (it was
+ multiplied with the rate matrix column-wise instead of row-wise).
+
+
+
+ CHANGES IN APE VERSION 2.5
NEW FEATURES
o The branch length score replaces the geodesic distance in dist.topo.
+ o Three new data sets are included: the gopher-lice data (gopher.D),
+ SO2 air pollution in 41 US cities (lmorigin.ex1, from Sokal &
+ Rohlf 1995), and some host-parasite specificity data
+ (lmorigin.ex2, from Legendre & Desdevises 2009).
+
BUG FIXES
to Otto Cordero for the fix).
+OTHER CHANGES
+
+ o The geodesic distance has been replaced by the branch length score
+ in dist.topo().
+
+
CHANGES IN APE VERSION 2.4-1
Package: ape
-Version: 2.5
-Date: 2010-02-01
+Version: 2.5-1
+Date: 2010-02-03
Title: Analyses of Phylogenetics and Evolution
Author: Emmanuel Paradis, Ben Bolker, Julien Claude, Hoa Sien Cuong, Richard Desper, Benoit Durand, Julien Dutheil, Olivier Gascuel, Gangolf Jobb, Christoph Heibl, Daniel Lawson, Vincent Lefort, Pierre Legendre, Jim Lemon, Yvonnick Noel, Johan Nylander, Rainer Opgen-Rhein, Korbinian Strimmer, Damien de Vienne
Maintainer: Emmanuel Paradis <Emmanuel.Paradis@ird.fr>
-## ace.R (2009-11-12)
+## ace.R (2010-02-03)
## Ancestral Character Estimation
-## Copyright 2005-2009 Emmanuel Paradis and Ben Bolker
+## Copyright 2005-2010 Emmanuel Paradis and Ben Bolker
## This file is part of the R-package `ape'.
## See the file ../COPYING for licensing issues.
table <- data.frame(ll, df, ddf, dev,
pchisq(dev, ddf, lower.tail = FALSE))
dimnames(table) <- list(1:length(X), c("Log lik.", "Df",
- "Df change", "Deviance",
+ "Df change", "Resid. Dev",
"Pr(>|Chi|)"))
structure(table, heading = "Likelihood Ratio Test Table",
class = c("anova", "data.frame"))
-## rTrait.R (2010-01-11)
+## rTrait.R (2010-02-03)
## Trait Evolution
for (i in N:1) x[des[i]] <- model(x[anc[i]], el[i])
} else {
diag(Q) <- -rowSums(Q)
+ freq <- rep(freq, each = k)
for (i in N:1) {
p <- matexpo(Q * freq * el[i])[x[anc[i]], ]
x[des[i]] <- .Internal(sample(k, size = 1, FALSE, prob = p))