Not an immediate issue but hoping avoid the warnings for the next CRAN submission of broom:
library(btergm)
#> Loading required package: xergm.common
#> Loading required package: ergm
#> Loading required package: statnet.common
#>
#> Attaching package: 'statnet.common'
#> The following object is masked from 'package:base':
#>
#> order
#> Loading required package: network
#> network: Classes for Relational Data
#> Version 1.13.0.1 created on 2015-08-31.
#> copyright (c) 2005, Carter T. Butts, University of California-Irvine
#> Mark S. Handcock, University of California -- Los Angeles
#> David R. Hunter, Penn State University
#> Martina Morris, University of Washington
#> Skye Bender-deMoll, University of Washington
#> For citation information, type citation("network").
#> Type help("network-package") to get started.
#>
#> ergm: version 3.8.0, created on 2017-08-18
#> Copyright (c) 2017, Mark S. Handcock, University of California -- Los Angeles
#> David R. Hunter, Penn State University
#> Carter T. Butts, University of California -- Irvine
#> Steven M. Goodreau, University of Washington
#> Pavel N. Krivitsky, University of Wollongong
#> Martina Morris, University of Washington
#> with contributions from
#> Li Wang
#> Kirk Li, University of Washington
#> Skye Bender-deMoll, University of Washington
#> Based on "statnet" project software (statnet.org).
#> For license and citation information see statnet.org/attribution
#> or type citation("ergm").
#> NOTE: Versions before 3.6.1 had a bug in the implementation of the
#> bd() constriant which distorted the sampled distribution somewhat.
#> In addition, Sampson's Monks datasets had mislabeled vertices. See
#> the NEWS and the documentation for more details.
#>
#> Attaching package: 'ergm'
#> The following objects are masked from 'package:statnet.common':
#>
#> colMeans.mcmc.list, sweep.mcmc.list
#>
#> Attaching package: 'xergm.common'
#> The following object is masked from 'package:ergm':
#>
#> gof
#> Loading required package: ggplot2
#> Warning: replacing previous import 'statnet.common::colMeans.mcmc.list' by
#> 'ergm::colMeans.mcmc.list' when loading 'ergm.count'
#> Warning: replacing previous import 'statnet.common::sweep.mcmc.list' by
#> 'ergm::sweep.mcmc.list' when loading 'ergm.count'
#> Warning: replacing previous import 'statnet.common::colMeans.mcmc.list' by
#> 'ergm::colMeans.mcmc.list' when loading 'tergm'
#> Warning: replacing previous import 'statnet.common::sweep.mcmc.list' by
#> 'ergm::sweep.mcmc.list' when loading 'tergm'
#> Warning: replacing previous import 'statnet.common::colMeans.mcmc.list' by
#> 'ergm::colMeans.mcmc.list' when loading 'statnet'
#> Warning: replacing previous import 'statnet.common::sweep.mcmc.list' by
#> 'ergm::sweep.mcmc.list' when loading 'statnet'
#> Warning: replacing previous import 'statnet.common::sweep.mcmc.list' by
#> 'ergm::sweep.mcmc.list' when loading 'btergm'
#> Warning: replacing previous import 'statnet.common::colMeans.mcmc.list' by
#> 'ergm::colMeans.mcmc.list' when loading 'btergm'
#> Package: btergm
#> Version: 1.9.1
#> Date: 2018-02-14
#> Authors: Philip Leifeld (University of Glasgow)
#> Skyler J. Cranmer (The Ohio State University)
#> Bruce A. Desmarais (Pennsylvania State University)
networks <- list()
for(i in 1:10){
mat <- matrix(rbinom(100, 1, .25), nrow = 10, ncol = 10)
diag(mat) <- 0
nw <- network::network(mat)
networks[[i]] <- nw
}
# Create 10 matrices as covariates
covariates <- list()
for (i in 1:10) {
mat <- matrix(rnorm(100), nrow = 10, ncol = 10)
covariates[[i]] <- mat
}
# Fit a model where the propensity to form ties depends
# on the edge covariates, controlling for the number of
# in-stars
btfit <- btergm(networks ~ edges + istar(2) +
edgecov(covariates), R = 100)
#>
#> Initial dimensions of the network and covariates:
#> t=1 t=2 t=3 t=4 t=5 t=6 t=7 t=8 t=9 t=10
#> networks (row) 10 10 10 10 10 10 10 10 10 10
#> networks (col) 10 10 10 10 10 10 10 10 10 10
#> covariates (row) 10 10 10 10 10 10 10 10 10 10
#> covariates (col) 10 10 10 10 10 10 10 10 10 10
#>
#> All networks are conformable.
#>
#> Dimensions of the network and covariates after adjustment:
#> t=1 t=2 t=3 t=4 t=5 t=6 t=7 t=8 t=9 t=10
#> networks (row) 10 10 10 10 10 10 10 10 10 10
#> networks (col) 10 10 10 10 10 10 10 10 10 10
#> covariates (row) 10 10 10 10 10 10 10 10 10 10
#> covariates (col) 10 10 10 10 10 10 10 10 10 10
#>
#> Starting pseudolikelihood estimation with 100 bootstrapping replications on a single computing core...
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Warning: 'term.list.formula' is deprecated.
#> Use 'list_rhs.formula' instead.
#> See help("Deprecated")
#> Done.
Happy to attach session info if it'll be useful to you.
Not an immediate issue but hoping avoid the warnings for the next CRAN submission of
broom:Happy to attach session info if it'll be useful to you.