internalFunctions {tapnet}

Helper functions for tapnet

Description

Lower-level, non-exported functions to be called by the main tapnet functions

Usage

internalFunctions()

pems_from_tree(tree)

select_relevant_pems(tree, species)

tmatch(delta_t, type = "normal", width = 1, shift = 0, err = 1e-05)

param_vec2list(params, n, m, fit.delta = FALSE)

loglik_tapnet(
  params,
  networks,
  tmatch_type_pem,
  tmatch_type_obs,
  lambda = 0,
  obj_function = "multinom",
  fit.delta = TRUE
)

latent_cor(true_pars, fitted_pars, pems_low, pems_high)

web_indices(web, web_dim, indices)

refit_params(tapnet, fit, fitted_I_mat)

Arguments

tree

phylogenetic tree in phylo format;

species

a named vector of species, representing (some of) the tips of the phylogenetic tree;

delta_t

vector of pairwise trait differences (higher - lower);

type

trait matching function: either "normal" or "shiftlnorm";

width

width parameter of trait matching function, similar to sd in the normal;

shift

shift parameter (optimum trait distance), currently ignored in fitting;

err

"baseline" probability of match, even if traits do not match at all;

params

parameter vector with setting for tapnet simulation;

n

number of latent trait linear combination parameters (lower level);

m

number of latent trait linear combination parameters (higher level);

fit.delta

logical; should the trait-weighting exponent delta be fitted?

networks

the "networks" part of a tapnet object;

tmatch_type_pem

type of trait matching function for latent traits;

tmatch_type_obs

type(s) of trait matching functions for observed traits; can be a vector as long as there are traits;

lambda

LASSO shrinkage parameter to avoid collinearity issues when observed traits are phylogenetically correlated;

obj_function

objective function, either "multinom" or anything else (currently anything else leads to OLS fitting);

true_pars

parameters used for simulating the network;

fitted_pars

parameters estimated by fit_tapnet;

pems_low

phylogenetic eigenvectors for the lower trophic level;

pems_high

phylogenetic eigenvectors for the higher trophic level;

web

data for an interaction network in vector form, e.g. from predict_tapnet;

web_dim

vector of two numbers indicating the rows and column of the network matrix;

indices

vector of names of network indices to compute; see networklevel for what is available;

tapnet

a tapnet object;

fit

a fitted tapnet;

fitted_I_mat

the fitted I-matrix of a fitted tapnet object (I think).

Details

They do roughly the following:

pems_from_tree

computes phylogenetic eigenvectors from a phylogenetic tree;

select_relevant_pems

identifies those phylogenetic eigenvectors (PEMs) of the full tree most relevant for a network containing only a subset of species;

tmatch

calculates interaction probabilities based on trait matching;

param_vec2list

converts a vector of parameters (for trait matching and latent trait combinations) into a named list;

loglik_tapnet

the log-likelihood function for fitting the tapnet model; actually quite an important function, easy to break, so not for the user to easily access;

latent_cor

computes correlation of fitted latent with true constructed traits for simulated data;

web_indices

computes the specified network indices for the provided network, after turning the prediction vector into a matrix;

refit_params

Simulate new networks from a fitted tapnet object, re-fit on the simulated network and output the parameter values.

Author(s)

Gita Benadi <[e-mail]>, Carsten Dormann <[e-mail]> and Jochen Fründ <[e-mail]>

References

Benadi et al. in prep