Description Usage Arguments Details Value Warning Author(s) References See Also Examples
Performs Phylogenetic linear regression evaluating intraspecific variability in response and/or predictor variables.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
formula |
The model formula: |
data |
Data frame containing species traits and species names as row names. |
phy |
A phylogeny (class 'phylo', see ? |
Vy |
Name of the column containing the standard deviation or the standard error of the response
variable. When information is not available for one taxon, the value can be 0 or |
Vx |
Name of the column containing the standard deviation or the standard error of the predictor
variable. When information is not available for one taxon, the value can be 0 or |
y.transf |
Transformation for the response variable (e.g. |
x.transf |
Transformation for the predictor variable (e.g. |
n.intra |
Number of times to repeat the analysis generating a random value for response and/or predictor variables.
If NULL, |
distrib |
A character string indicating which distribution to use to generate a random value for the response
and/or predictor variables. Default is normal distribution: "normal" (function |
model |
The phylogenetic model to use (see Details). Default is |
track |
Print a report tracking function progress (default = TRUE) |
... |
Further arguments to be passed to |
This function fits a phylogenetic linear regression model using phylolm
.
The regression is repeated n.intra
times. At each iteration the function generates a random value
for each row in the dataset using the standard deviation or errors supplied and assuming a normal or uniform distribution.
To calculate means and se for your raw data, you can use the summarySE
function from the
package Rmisc
.
#' All phylogenetic models from phylolm
can be used, i.e. BM
,
OUfixedRoot
, OUrandomRoot
, lambda
, kappa
,
delta
, EB
and trend
. See ?phylolm
for details.
Currently, this function can only implement simple linear models (i.e. trait~ predictor). In the future we will implement more complex models.
Output can be visualised using sensi_plot
.
The function intra_phylm
returns a list with the following
components:
formula
: The formula
data
: Original full dataset
sensi.estimates
: Coefficients, aic and the optimised
value of the phylogenetic parameter (e.g. lambda
) for each regression.
N.obs
: Size of the dataset after matching it with tree tips and removing NA's.
stats
: Main statistics for model parameters.CI_low
and CI_high
are the lower
and upper limits of the 95
all.stats
: Complete statistics for model parameters. sd_intra
is the standard deviation
due to intraspecific variation. CI_low
and CI_high
are the lower and upper limits
of the 95
sp.pb
: Species that caused problems with data transformation (see details above).
When Vy or Vx exceed Y or X, respectively, negative (or null) values can be generated, this might cause problems
for data transformation (e.g. log-transformation). In these cases, the function will skip the simulation. This problem can
be solved by increasing n.intra
, changing the transformation type and/or checking the target species in output$sp.pb.
Caterina Penone & Pablo Ariel Martinez
Paterno, G. B., Penone, C. Werner, G. D. A. sensiPhy: An r-package for sensitivity analysis in phylogenetic comparative methods. Methods in Ecology and Evolution 2018, 9(6):1461-1467
Martinez, P. a., Zurano, J.P., Amado, T.F., Penone, C., Betancur-R, R., Bidau, C.J. & Jacobina, U.P. (2015). Chromosomal diversity in tropical reef fishes is related to body size and depth range. Molecular Phylogenetics and Evolution, 93, 1-4
Ho, L. S. T. and Ane, C. 2014. "A linear-time algorithm for Gaussian and non-Gaussian trait evolution models". Systematic Biology 63(3):397-408.
1 2 3 4 5 6 7 8 9 | # Load data:
data(alien)
# run PGLS accounting for intraspecific variation:
intra <- intra_phylm(gestaLen ~ adultMass, y.transf = log, x.transf = log,
phy = alien$phy[[1]], data = alien$data, Vy = "SD_gesta", n.intra = 30)
# To check summary results:
summary(intra)
# Visual diagnostics
sensi_plot(intra)
|
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