Error(s) in re-building vignettes:
--- re-building ‘nmaINLA.Rnw’ using knitr
Loading required package: INLA
Loading required package: Matrix
Loading required package: sp
Loading required package: parallel
This is INLA_19.09.03 built 2020-01-26 06:43:17 UTC.
See www.r-inla.org/contact-us for how to get help.
To enable PARDISO sparse library; see inla.pardiso()
Loading required package: nmaINLA
 ----------- FAILURE REPORT -------------- 
 --- failure: the condition has length > 1 ---
 --- srcref --- 
: 
 --- package (from environment) --- 
nmaINLA
 --- call from context --- 
nma_inla(SmokdatINLA, likelihood = "binomial", fixed.par = c(0, 
    1000), tau.prior = "uniform", tau.par = c(0, 5), type = "consistency")
 --- call from argument --- 
if (class(try.tau) != "try-error") {
    tau.stdev = sqrt(INLA::inla.emarginal(function(x) x^2, tau) - 
        INLA::inla.emarginal(function(x) x^1, tau)^2)
} else {
    tau.stdev = NA
}
 --- R stacktrace ---
where 1 at <text>#12: nma_inla(SmokdatINLA, likelihood = "binomial", fixed.par = c(0, 
    1000), tau.prior = "uniform", tau.par = c(0, 5), type = "consistency")
where 2: eval(expr, envir, enclos)
where 3: eval(expr, envir, enclos)
where 4: withVisible(eval(expr, envir, enclos))
where 5: withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler, 
    error = eHandler, message = mHandler)
where 6: handle(ev <- withCallingHandlers(withVisible(eval(expr, envir, 
    enclos)), warning = wHandler, error = eHandler, message = mHandler))
where 7: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval(expr, 
    envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)))
where 8: evaluate_call(expr, parsed$src[[i]], envir = envir, enclos = enclos, 
    debug = debug, last = i == length(out), use_try = stop_on_error != 
        2L, keep_warning = keep_warning, keep_message = keep_message, 
    output_handler = output_handler, include_timing = include_timing)
where 9: evaluate::evaluate(...)
where 10: evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning), 
    keep_message = !isFALSE(options$message), stop_on_error = if (options$error && 
        options$include) 0L else 2L, output_handler = knit_handlers(options$render, 
        options))
where 11: in_dir(input_dir(), evaluate(code, envir = env, new_device = FALSE, 
    keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message), 
    stop_on_error = if (options$error && options$include) 0L else 2L, 
    output_handler = knit_handlers(options$render, options)))
where 12: block_exec(params)
where 13: call_block(x)
where 14: process_group.block(group)
where 15: process_group(group)
where 16: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), 
    error = function(e) {
        setwd(wd)
        cat(res, sep = "\n", file = output %n% "")
        message("Quitting from lines ", paste(current_lines(i), 
            collapse = "-"), " (", knit_concord$get("infile"), 
            ") ")
    })
where 17: process_file(text, output)
where 18: (if (grepl("\\.[Rr]md$", file)) knit2html_v1 else if (grepl("\\.[Rr]rst$", 
    file)) knit2pandoc else knit)(file, encoding = encoding, 
    quiet = quiet, envir = globalenv(), ...)
where 19: engine$weave(file, quiet = quiet, encoding = enc)
where 20: doTryCatch(return(expr), name, parentenv, handler)
where 21: tryCatchOne(expr, names, parentenv, handlers[[1L]])
where 22: tryCatchList(expr, classes, parentenv, handlers)
where 23: tryCatch({
    engine$weave(file, quiet = quiet, encoding = enc)
    setwd(startdir)
    output <- find_vignette_product(name, by = "weave", engine = engine)
    if (!have.makefile && vignette_is_tex(output)) {
        texi2pdf(file = output, clean = FALSE, quiet = quiet)
        output <- find_vignette_product(name, by = "texi2pdf", 
            engine = engine)
    }
    outputs <- c(outputs, output)
}, error = function(e) {
    thisOK <<- FALSE
    fails <<- c(fails, file)
    message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s", 
        file, conditionMessage(e)))
})
where 24: tools:::buildVignettes(dir = "/data/gannet/ripley/R/packages/tests-devel/nmaINLA.Rcheck/vign_test/nmaINLA", 
    ser_elibs = "/tmp/RtmpUmlHVI/file439f754f841f.rds")

 --- value of length: 2 type: logical ---
[1] TRUE TRUE
 --- function from context --- 
function (datINLA, likelihood = NULL, fixed.par = c(0, 1000), 
    tau.prior = "uniform", tau.par = c(0, 5), kappa.prior = "uniform", 
    kappa.par = c(0, 5), mreg = FALSE, type = "consistency", 
    verbose = FALSE, inla.strategy = "simplified.laplace", improve.hyperpar.dz = 0.75, 
    correct = FALSE, correct.factor = 10, improve.hyperpar = TRUE) 
{
    if (requireNamespace("INLA", quietly = TRUE)) {
        if (!(sum(search() == "package:INLA")) == 1) {
            stop("INLA need to be loaded! \n\n           Please use the following command to load INLA,\n\n           library(INLA) \n")
        }
        if (!is.data.frame(datINLA)) {
            stop("Data MUST be a data frame!!!")
        }
        if (likelihood %in% c("binomial", "normal", "poisson") == 
            FALSE) {
            stop("Function argument \"likelihood\" must be equal to \"binomial\" or \"normal\" or \"poisson\" !!!")
        }
        if (type %in% c("FE", "consistency", "jackson") == FALSE) {
            stop("Function argument \"type\" must be equal to \"FE\" or \"consistency\" or \"jackson\" !!!")
        }
        if (tau.prior %in% c("uniform", "half-normal") == FALSE) {
            stop("Function argument \"tau.prior\" must be equal to \"uniform\" or \"half-normal\" !!!")
        }
        if (kappa.prior %in% c("uniform", "half-normal") == FALSE) {
            stop("Function argument \"kappa.prior\" must be equal to \"uniform\" or \"half-normal\" !!!")
        }
        cor <- 0.5
        ngroup <- max(datINLA$na) - 1
        cor.inla.init <- log((1 + cor * (ngroup - 1))/(1 - cor))
        N <- max(datINLA$study)
        d_params <- grep("d1", names(datINLA), value = TRUE)
        N_d_params <- length(d_params)
        inla.form <- paste("Y ~ -1 + mu +", paste(d_params, collapse = "+", 
            sep = " "), sep = " ")
        if (mreg == TRUE) {
            inla.form <- paste(inla.form, " + cov", sep = "")
        }
        if (type %in% c("consistency", "jackson") == TRUE) {
            hyperunif.function <- function(x) {
                ifelse(exp(x)^-0.5 < tau.par[2] & exp(x)^-0.5 > 
                  tau.par[1], logdens <- log(1/(tau.par[2] - 
                  tau.par[1])), logdens <- log(9.98012604599318e-322))
                logdenst <- logdens + log(0.5 * exp(-x/2))
                return(logdenst)
            }
            lprec <- seq(from = -40, to = 40, len = 20000)
            unif.prior.table <- paste(c("table:", cbind(lprec, 
                sapply(lprec, FUN = hyperunif.function))), sep = "", 
                collapse = " ")
            if (tau.prior == "uniform") {
                het.expr <- " + f(het, model=\"iid\", hyper = list(theta = list(prior = unif.prior.table)"
            }
            if (tau.prior == "half-normal") {
                tau.par[2] <- 1/tau.par[2]
                het.expr <- " + f(het, model=\"iid\", hyper = list(theta = list(prior = \"logtnormal\", param = tau.par)"
            }
            multi.arm.expr <- ", group = g, control.group = list(model = \"exchangeable\", hyper = list(rho = list(fixed = TRUE, initial = cor.inla.init)))"
            inla.form <- paste(inla.form, het.expr, ")", sep = "")
            inla.form <- paste(inla.form, multi.arm.expr, ")", 
                sep = "")
        }
        if (type == "jackson") {
            if (kappa.prior == "uniform") {
                inc.expr <- " + f(inc, model=\"iid\", hyper = list(theta = list(prior = unif.prior.table)"
            }
            if (kappa.prior == "half-normal") {
                kappa.par[2] <- 1/kappa.par[2]
                inc.expr <- " + f(inc, model=\"iid\", hyper = list(theta = list(prior = \"logtnormal\", param = kappa.par)"
            }
            inla.form <- paste(inla.form, inc.expr, ")", sep = "")
            inla.form <- paste(inla.form, multi.arm.expr, ")", 
                sep = "")
        }
        if (likelihood == "binomial") {
            datINLA$Y = datINLA$responders
            Ntrials = datINLA$sampleSize
            fit.inla <- INLA::inla(stats::as.formula(inla.form), 
                data = datINLA, family = "binomial", verbose = verbose, 
                control.fixed = list(expand.factor.strategy = "inla", 
                  mean = fixed.par[1], prec = 1/fixed.par[2]), 
                Ntrials = Ntrials, control.compute = list(dic = TRUE, 
                  waic = TRUE, cpo = TRUE, mlik = TRUE, config = TRUE), 
                control.inla = list(strategy = inla.strategy, 
                  correct = correct, correct.factor = correct.factor))
        }
        if (likelihood == "normal") {
            datINLA$Y = datINLA$mean
            prec = 1/datINLA$std.err^2
            fit.inla <- INLA::inla(stats::as.formula(inla.form), 
                family = "normal", verbose = verbose, data = datINLA, 
                control.fixed = list(expand.factor.strategy = "inla", 
                  mean = fixed.par[1], prec = 1/fixed.par[2]), 
                control.family = list(hyper = list(prec = list(fixed = TRUE, 
                  initial = 0))), scale = prec, control.compute = list(dic = TRUE, 
                  waic = TRUE, cpo = TRUE, mlik = TRUE, config = TRUE), 
                control.inla = list(strategy = inla.strategy, 
                  correct = correct, correct.factor = correct.factor))
        }
        if (likelihood == "poisson") {
            datINLA$Y = datINLA$responders
            E = datINLA$exposure
            fit.inla <- INLA::inla(stats::as.formula(inla.form), 
                data = datINLA, family = "poisson", verbose = verbose, 
                control.fixed = list(expand.factor.strategy = "inla", 
                  mean = fixed.par[1], prec = 1/fixed.par[2]), 
                E = E, control.compute = list(dic = TRUE, waic = TRUE, 
                  cpo = TRUE, mlik = TRUE, config = TRUE), control.inla = list(strategy = inla.strategy, 
                  correct = correct, correct.factor = correct.factor))
        }
        if (!fit.inla$ok) {
            stop("Something wrong while running model with data! Please set verbose = TRUE to check!!!!")
        }
        if (type %in% c("consistency", "jackson") == TRUE) {
            if (improve.hyperpar == TRUE) {
                fit.inla <- INLA::inla.hyperpar(fit.inla, dz = improve.hyperpar.dz)
            }
        }
        d_params <- as.matrix(fit.inla$summary.fixed[(N + 1):(N + 
            N_d_params), c(1, 2, 3, 4, 5)])
        if (mreg == TRUE) {
            cov <- as.matrix(fit.inla$summary.fixed[N + N_d_params + 
                1, c(1, 2, 3, 4, 5)])
        }
        if (type %in% c("consistency", "jackson") == TRUE) {
            tau.mean <- INLA::inla.emarginal(function(x) 1/sqrt(x), 
                fit.inla$marginals.hyperpar[["Precision for het"]])
            try.tau = try(tau <- INLA::inla.tmarginal(function(x) 1/sqrt(x), 
                fit.inla$marginals.hyperpar[["Precision for het"]]), 
                silent = TRUE)
            if (class(try.tau) != "try-error") {
                tau.stdev = sqrt(INLA::inla.emarginal(function(x) x^2, 
                  tau) - INLA::inla.emarginal(function(x) x^1, 
                  tau)^2)
            }
            else {
                tau.stdev = NA
            }
            tau.quant <- as.numeric(rev(sqrt((1/summary(fit.inla)$hyperpar[1, 
                c(3, 4, 5)]))))
            if (type == "jackson") {
                kappa.mean <- INLA::inla.emarginal(function(x) 1/sqrt(x), 
                  fit.inla$marginals.hyperpar[["Precision for inc"]])
                try.kappa = try(kappa <- INLA::inla.tmarginal(function(x) 1/sqrt(x), 
                  fit.inla$marginals.hyperpar[["Precision for inc"]]), 
                  silent = TRUE)
                if (class(try.kappa) != "try-error") {
                  kappa.stdev = sqrt(INLA::inla.emarginal(function(x) x^2, 
                    kappa) - INLA::inla.emarginal(function(x) x^1, 
                    kappa)^2)
                }
                else {
                  kappa.stdev = NA
                }
                kappa.quant <- as.numeric(rev(sqrt((1/summary(fit.inla)$hyperpar[2, 
                  c(3, 4, 5)]))))
                tab <- matrix(NA, 2, 5)
                tab[1, ] <- c(tau.mean, tau.stdev, tau.quant[1], 
                  tau.quant[2], tau.quant[3])
                tab[2, ] <- c(kappa.mean, kappa.stdev, kappa.quant[1], 
                  kappa.quant[2], kappa.quant[3])
            }
            else {
                tab <- matrix(NA, 1, 5)
                rownames(tab) <- "tau"
            }
            tab[1, ] <- c(tau.mean, tau.stdev, tau.quant[1], 
                tau.quant[2], tau.quant[3])
            colnames(tab) <- c("mean", "sd", "0.025quant", "0.5quant", 
                "0.975quant")
        }
        else tab <- NA
        fit.inla$d_params <- d_params
        if (mreg == TRUE) {
            fit.inla$cov <- cov
        }
        fit.inla$hyperpar <- tab
        fit.inla$fixed.par <- fixed.par
        fit.inla$tau.prior <- tau.prior
        fit.inla$tau.par <- tau.par
        fit.inla$kappa.prior <- kappa.prior
        fit.inla$kappa.par <- kappa.par
        fit.inla$type <- type
        fit.inla$mreg <- mreg
        fit.inla$inla.strategy <- inla.strategy
        fit.inla$N <- N
        fit.inla$N_d_params <- N_d_params
        class(fit.inla) <- "nma_inla"
        return(fit.inla)
    }
    else {
        stop("INLA need to be installed and loaded!\n\nPlease use the following command to install and load INLA,\n\ninstall.packages(\"INLA\", repos=c(getOption(\"repos\"), INLA=\"https://inla.r-inla-download.org/R/stable\"), dep=TRUE) \n\nlibrary(INLA) \n")
    }
}
<bytecode: 0xe7c9950>
<environment: namespace:nmaINLA>
 --- function search by body ---
Function nma_inla in namespace nmaINLA has this body.
 ----------- END OF FAILURE REPORT -------------- 
Quitting from lines 99-142 (nmaINLA.Rnw) 
Error: processing vignette 'nmaINLA.Rnw' failed with diagnostics:
the condition has length > 1
--- failed re-building ‘nmaINLA.Rnw’

SUMMARY: processing the following file failed:
  ‘nmaINLA.Rnw’

Error: Vignette re-building failed.
Execution halted