CRAN Package Check Results for Package CBnetworkMA

Last updated on 2024-06-14 05:58:17 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.0 6.19 32.08 38.27 OK
r-devel-linux-x86_64-debian-gcc 0.1.0 4.80 22.98 27.78 ERROR
r-devel-linux-x86_64-fedora-clang 0.1.0 47.38 OK
r-devel-linux-x86_64-fedora-gcc 0.1.0 46.01 OK
r-devel-windows-x86_64 0.1.0 8.00 49.00 57.00 OK
r-patched-linux-x86_64 0.1.0 5.79 30.26 36.05 OK
r-release-linux-x86_64 0.1.0 6.10 31.25 37.35 OK
r-release-macos-arm64 0.1.0 20.00 OK
r-release-macos-x86_64 0.1.0 29.00 OK
r-release-windows-x86_64 0.1.0 9.00 16.00 25.00 FAIL
r-oldrel-macos-arm64 0.1.0 30.00 OK
r-oldrel-macos-x86_64 0.1.0 45.00 OK
r-oldrel-windows-x86_64 0.1.0 9.00 52.00 61.00 OK

Check Details

Version: 0.1.0
Check: package dependencies
Result: NOTE Package suggested but not available for checking: ‘igraph’ Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1.0
Check: examples
Result: ERROR Running examples in ‘CBnetworkMA-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: networkMA > ### Title: Contrast-Based Bayesian Network Meta-Analysis Model > ### Aliases: networkMA > > ### ** Examples > > > > > # This number of MCMC samples is for illustrative purposes only, it may > # be necessary to increase the total > ni <- 10000 > nb <- 5000 > nt <- 5 > > dat <- smoking # Use the smoking cessation dataset. > > # total number of treatments > K <- length(unique(dat$tid)) > > # Fit model 1 > set.seed(101) > # Fit the Guassian Effects model. > m1 <- networkMA(dat, model="gaussian", niter=ni, nburn=nb, nthin=nt, + mb=0, sb=10, md=0, sd=1, + tau_prior = "lognormal", tau_lm = -2.34, tau_lsd = 2, + mh=c(0.5, 0.5, 0.05, 0.5)) > > mean(m1$d1[,2]) [1] 0.3956062 > quantile(m1$d1[,2], c(0.025, 0.975)) 2.5% 97.5% -0.1752734 0.9893580 > > # Fit the DP Gaussian base measure model. > m2 <- networkMA(dat, model="dp_gaussian", niter=ni, nburn=nb, nthin=nt, + mb=0, sb=10, md=0, sd=1, + tau_prior = "lognormal", tau_lm = -2.34, tau_lsd = 2, + alpha=1, + mh=c(0.5, 0.5, 0.05, 0.5)) > > mean(m2$d1[,2]) [1] 0.5964177 > quantile(m2$d1[,2], c(0.025, 0.975)) 2.5% 97.5% -0.06574574 1.02003591 > > > # Fit the DP spike and slab base measure model. > m3 <- networkMA(dat, model="dp_spike_slab", niter=ni, nburn=nb, nthin=nt, + mb=0, sb=10, md=0, sd=1, + tau_prior = "lognormal", tau_lm = -2.34, tau_lsd = 2, + alpha=1, aw=1, bw=1, v0=0.1, scale=1, nu=1, + mh=c(0.5, 0.5, 0.05, 0.5)) > > mean(m3$d1[,2]) [1] 0.5110981 > quantile(m3$d1[,2], c(0.025, 0.975)) 2.5% 97.5% -0.03322983 1.04003997 > > # Function that finds the graph corresponding to the posterior samples, and > # graphs for a sequence of threshold probabilities (denoted as gamma in > # the article) > > gamma_vec <- c(0.5, 0.75, 0.9, 0.95, 0.99) > networks <- network_graphs(m3[["ordmat"]], gamma=gamma_vec) > > > # One way of plotting the directed graph based on the output of the function > # above is the following. The "igraph" package can be used to facilitate > # producing pair-wise graphical model display > > > oldpar <- par(no.readonly = TRUE) > > > # Plot network that corresponds to posterior mode > Network = networks[[1]] > out = cbind(from=1:ncol(Network),to=1:ncol(Network),color=0) > for(i in 1:(ncol(Network)-1)){ + for(j in (i+1):ncol(Network)){ + if(Network[i,j]==1) out = rbind(out,c(i,j,2)) + if(Network[i,j]==-1)out = rbind(out,c(j,i,2)) + if(Network[i,j]==0) out = rbind(out,c(i,j,1),c(j,i,1)) + } + } > > > mynet <- igraph::graph_from_data_frame(out,directed = TRUE) Error in loadNamespace(x) : there is no package called ‘igraph’ Calls: loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1.0
Check: package dependencies
Result: FAIL
Flavor: r-release-windows-x86_64