data.frame() were adjusted to work
with stringsAsFactors = FALSE or stringsAsFactors = TRUE.This new version fix a small bug with functions for phylogenetic uncertainty (tree_xxx). Minor typos were also fixed.
This new version fix all issues requested by CRAN. In all sensiPhy functions the use of if() with conditions of length greater than one was corrected to avoid Errors.
The vigentee now include two new sections:
1. Using sensiPhy to analyse results from other packages
2. How long does it take?
Also available at the online tutorial: https://github.com/paternogbc/sensiPhy/wiki
sensiPhy now performs sensitivity analysis for a new
class of methods which allows users to perform sensitivity analyses of
both continuous and discrete (binary) macro-evolutionary models of trait
evolution (e.g. Mkn models for binary traits, OU, BM, lambda etc. for
continuous traits).
sensiPhy nor performs sensitivity analysis of
phylogenetic uncertainty for simple metrics of diversification and
speciation rates (Magallon and Sanderson (2000) method) or speciation
rate using bd.km (Kendall-Moran method)
influ_continuous(): Performs sensitivity analysis of
influential species for models of trait evolution (continuous
characters)
influ_discrete(): Performs sensitivity analysis of
influential species for models of trait evolution (binary discrete
characters)
clade_continuous(): Performs sensitivity analysis of
influential clades for models of trait evolution (continuous
characters)
clade_discrete(): Performs sensitivity analysis of
influential clades for for models of trait evolution (binary discrete
characters)
samp_continuous(): Performs sensitivity analysis of
species sampling for models of trait evolution (continuous
characters)
samp_discrete(): Performs sensitivity analysis of
species sampling for models of trait evolution (binary discrete
characters)
tree_continuous(): Performs sensitivity analysis of
phylogenetic uncertainty for models of trait evolution (continuous
characters)
tree_discrete(): Performs sensitivity analysis of
phylogenetic uncertainty for models of trait evolution (binary discrete
characters)
tree_bd(): Performs estimates of diversification rate
evaluating uncertainty in trees topology.summary() and sensi_plot methods were
implemented (for all new functions) to provide a quick and intuitive
overview of results from sensitivite analysis.sensiPhy now imports the package
phytools
sensiPhy now performs sensitivity analysis by
interacting two types of uncertainty at the same time (tree and intra
against influ, clade and samp methods)sensiPhy now performs sensitivity analysis for
phylogenetic signalinflu_physig(): Performs sensitivity analysis of
influential species for phylogenetic signal estimate (k or lambda)clade_physig(): Performs sensitivity analysis of
influential clades for phylogenetic signal estimate (k or lambda)samp_physig(): Performs sensitivity analysis of species
sampling for phylogenetic signal estimate (k or lambda)tree_physig(): Performs sensitivity analysis of
phylogenetic signal estimate (k or lambda) accounting for phylogenetic
uncertaintyintra_physig(): Performs sensitivity analysis of
phylogenetic signal estimate (k or lambda) accounting for intra-specific
variation and measurement errors ##### Interactions for phylolm
modelstree_intra_phylm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and intraspecific
variability for phylolm models (linear regression)tree_intra_phyglm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and intraspecific
variability for phylolm models (logistic regression)tree_clade_phylm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and sensitivity to species
sampling for phylolm models (linear regression)tree_clade_phyglm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and sensitivity to species
sampling for phylolm models (logistic regression)tree_influ_phylm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and influential species
detection for phylolm models (linear regression)tree_influ_phyglm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and influential species
detection for phylolm models (logistic regression)tree_samp_phylm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and sensitivity to species
sampling for phylolm models (linear regression)tree_samp_phyglm(): Performs sensitivity analysis of
interaction between phylogenetic uncertainty and sensitivity to species
sampling for phylolm models (logistic regression)intra_clade_phylm(): Performs sensitivity analysis of
interaction between intraspecific variability and influential clades for
phylolm models (linear regression)intra_clade_phyglm(): Performs sensitivity analysis of
interaction between intraspecific variability and influential clades for
phylolm models (logistic regression)intra_influ_phylm(): Performs sensitivity analysis of
interaction between intraspecific variability and influential species
detection for phylolm models (linear regression)intra_influ_phyglm(): Performs sensitivity analysis of
interaction between intraspecific variability and influential species
detection for phylolm models (logistic regression)intra_samp_phylm(): Performs sensitivity analysis of
interaction between intraspecific variability and species sampling for
phylolm models (linear regression)intra_samp_phyglm(): Performs sensitivity analysis of
interaction between intraspecific variability and species sampling for
phylolm models (logistic regression)match_data_phy() now accepts datasets with no
information on species names as row names. If the number of species
corresponds to the number of tips a warning informs the user that the
function assumes that the dataset and the phylogeny are in the same
order.sensiPhy function the following changes were
made:Treemethods: Data order was matching order of the first
tree of the multiphylo file only. This bug is now fixed. Data and order
matching is now done at each iteration.miss.phylo.d() - Calculates phylogenetic signal for
missing data (D statistic; Fritz & Purvis 2010). Missingness is
recoded into a binary variable.The package now includes a Vignette with a quick introduction to all sensiPhy functions.
clade_phylm() and clade_phyglm() now
account for clade sample size bias. This is done by estimating a null
distribution of intercepts and slopes considering only the number of
species in the clade.
summary() methods for clade_phylm()
& clade_phyglm() now includes a randomization test to
account for the number of species in clades (tests if change in model
parameters (without the focal clade) is within the null distribution -
one-tailed test).
sensi_plot() for clade analysis now include a
histogram with the simulated DFslopes (null distribution).
sensi_plot() for influential species analysis
(influ_phylm / influ_phyglm) now prints the
names of the most influential species on the regression plot.
sensi_plot() now uses font size = 12 for better
visualization.
Packages datasets (“primates”, “alien”) now loads data and phylogeny in independent objects to faciliate usage in examples.
First submission to CRAN.