* using log directory ‘/data/gannet/ripley/R/packages/tests-LENGTH1/MsdeParEst.Rcheck’
* using R Under development (unstable) (2022-04-03 r82074)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* using option ‘--no-stop-on-test-error’
* checking for file ‘MsdeParEst/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘MsdeParEst’ version ‘1.7’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘MsdeParEst’ can be installed ... [18s/37s] OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking use of S3 registration ... OK
* checking dependencies in R code ... NOTE
Namespaces in Imports field not imported from:
  ‘MASS’ ‘moments’ ‘mvtnorm’
  All declared Imports should be used.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [30s/49s] OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd line widths ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking examples ... [8s/11s] ERROR
Running examples in ‘MsdeParEst-Ex.R’ failed
The error most likely occurred in:

> ### Name: msde.sim
> ### Title: Simulation Of A Mixed Stochastic Differential Equation
> ### Aliases: msde.sim
> 
> ### ** Examples
> 
> 
>  
>  # Example 1 : one random effect in the drift and one fixed effect in the diffusion coefficient
>  sim <- msde.sim(M = 30, T = 1, N = 1000, model = 'OU', drift.random = 2,
+                 diffusion.random = 0, drift.param = c(0,1,sqrt(0.4/4)), diffusion.param = 0.5)
Be careful, X0 is missing thus the initial value X0=0.01 is used
>                 
>  # Example 2 : two random effects in the drift and one random effect in the diffusion coefficient
> 
>  sim <- msde.sim(M = 30, T = 1, N = 1000, model = 'OU', drift.random = c(1,2),
+                 diffusion.random = 1, drift.param = c(1,0.5,0.5,0.5), diffusion.param = c(8,1/2))
Be careful, X0 is missing thus the initial value X0=0.01 is used
 ----------- FAILURE REPORT -------------- 
 --- failure: length > 1 in coercion to logical ---
 --- srcref --- 
: 
 --- package (from environment) --- 
MsdeParEst
 --- call from context --- 
msde.sim(M = 30, T = 1, N = 1000, model = "OU", drift.random = c(1, 
    2), diffusion.random = 1, drift.param = c(1, 0.5, 0.5, 0.5), 
    diffusion.param = c(8, 1/2))
 --- call from argument --- 
(drift.random == 0) && (length(drift.param) != 2)
 --- R stacktrace ---
where 1: msde.sim(M = 30, T = 1, N = 1000, model = "OU", drift.random = c(1, 
    2), diffusion.random = 1, drift.param = c(1, 0.5, 0.5, 0.5), 
    diffusion.param = c(8, 1/2))

 --- value of length: 2 type: logical ---
[1] FALSE FALSE
 --- function from context --- 
function (M, T, N = 100, model, drift.random, diffusion.random, 
    drift.param, diffusion.param, nb.mixt = 1, mixt.prop = 1, 
    t0 = 0, X0 = 0.01, delta = T/N, op.plot = 0, add.plot = FALSE) 
{
    con <- file(tempfile(), open = "w")
    on.exit(close(con))
    sde.sim <- function(...) {
        sink(con)
        res <- sde::sde.sim(...)
        sink(NULL)
        res
    }
    if (((M - round(M)) != 0) || (M <= 0)) {
        stop("Invalid value for M. The number of simulated trajectories should be a positive integer")
    }
    if (((N - round(N)) != 0) || (N <= 0)) {
        stop("Invalid value for N. The number of simulated time points should be a positive integer")
    }
    if (t0 < 0) {
        stop("Invalid value for t0. The starting time point should be positive")
    }
    if (T <= 0) {
        stop("Invalid value for T. The maximum time point should be positive")
    }
    if (t0 > T) {
        stop("The starting time point t0 should be smaller than the maximum time point T")
    }
    if ((delta < 0) || (delta > (T - t0))) {
        stop("Invalid value for delta")
    }
    if ((model != "OU") & (model != "CIR")) {
        stop("A model must be precised: OU or CIR")
    }
    if (((nb.mixt - round(nb.mixt)) != 0) || (nb.mixt <= 0)) {
        stop("The number of mixture components (nb.mixt) should be a positive integer")
    }
    if ((diffusion.random != 0) && (diffusion.random != 1)) {
        stop("Invalid value for diffusion.random, should be either 0 or 1")
    }
    valid.drift = list(0, 1, 2, c(1, 2))
    check <- 0
    for (i in 1:4) {
        check <- check + prod(drift.random %in% valid.drift[[i]])
    }
    if (check == 0) {
        stop("Invalid value for drift.random, should be either 0, or 1, or 2, or c(1,2)")
    }
    if ((model == "CIR") && (X0 <= 0)) {
        stop("For the CIR model, the initial values should be positive.")
    }
    if (missing(X0)) {
        message("Be careful, X0 is missing thus the initial value X0=0.01 is used")
    }
    if ((diffusion.random == 1) && (length(diffusion.param) != 
        2)) {
        stop("Invalid diffusion.param, should be a vector of length 2")
    }
    if ((diffusion.random == 0) && (length(diffusion.param) > 
        1)) {
        message("Only the first value of diffusion.param is considered")
    }
    if (prod(diffusion.param > 0) != 1) {
        stop("Invalid diffusion.param, should contain positive values")
    }
    if (nb.mixt == 1) {
        if ((drift.random == 0) && (length(drift.param) != 2)) {
            stop("Invalid drift.param, should be a vector of length 2")
        }
        if (((sum(drift.random) == 1) || (sum(drift.random) == 
            2)) && (length(drift.param) != 3)) {
            stop("Invalid drift.param, should be a vector of length 3")
        }
        if ((sum(drift.random) == 3) && (length(drift.param) != 
            4)) {
            stop("Invalid drift.param, should be a vector of length 4")
        }
    }
    else {
        if (dim(drift.param)[1] != nb.mixt) {
            stop("Invalid dimensions for drift.param, should have as many lines as mixture components")
        }
        if (((sum(drift.random) == 1) || (sum(drift.random) == 
            2)) && (dim(drift.param)[2] != 3)) {
            stop("Invalid dimensions for drift.param, should have 3 columns")
        }
        if ((sum(drift.random) == 3) && (dim(drift.param)[2] != 
            4)) {
            stop("Invalid dimensions for drift.param, should have 4 columns")
        }
    }
    if (((sum(drift.random)) == 0) && (diffusion.random == 0)) {
        stop("There should be at least one random effect either in the drift or the diffusion coefficient.")
    }
    if (((diffusion.random == 1) && (nb.mixt > 1))) {
        stop("If there is one random effect in the diffusion coefficient, the random effects in the drift can't follow a mixture of Normal distributions. Try nb.mixt = 1.")
    }
    if (length(mixt.prop) != nb.mixt) {
        stop("There should be as many mixing proportions as mixture components")
    }
    if ((prod(mixt.prop >= 0) == 0)) {
        stop("Invalid values for the mixing proportions, should be positive")
    }
    else {
        if (prod(mixt.prop <= 1) == 0) {
            mixt.prop <- mixt.prop/sum(mixt.prop)
        }
    }
    delta <- T/N
    times <- seq(t0, T, length = N + 1)
    X <- matrix(0, M, N + 1)
    index <- NA
    if (diffusion.random == 0) {
        sig <- diffusion.param[1]
        psi <- NA
        if ((sum(drift.random) > 2)) {
            phi <- matrix(0, 2, M)
            if (nb.mixt == 1) {
                phi[1, ] <- rnorm(M, drift.param[1], drift.param[2])
                phi[2, ] <- rnorm(M, drift.param[3], drift.param[4])
            }
            if (nb.mixt > 1) {
                phi <- mixture.sim(M, drift.param, mixt.prop)$Y
            }
            if (model == "OU") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(T = T, X0 = X0, 
                    N = N, delta = delta, method = "EA", theta = c(phi[, 
                      j], sig), model = "OU"))
                }
            }
            if (model == "CIR") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(T = T, X0 = X0, 
                    N = N, delta = delta, method = "milstein", 
                    theta = c(phi[, j], sig), sigma.x = expression(sig/(2 * 
                      sqrt(x))), sigma = expression(sig * sqrt(x)), 
                    model = "CIR"))
                }
            }
        }
        if (sum(drift.random) == 1) {
            phi <- rep(0, M)
            if (nb.mixt > 1) {
                sim <- mixture.sim(M, drift.param[, c(1, 2)], 
                  mixt.prop)
                phi <- sim$Y
                index <- sim$index
                if (model == "OU") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(T = T, 
                      X0 = X0, N = N, delta = delta, method = "EA", 
                      theta = c(phi[j], drift.param[index[j], 
                        3], sig), model = "OU"))
                  }
                }
                if (model == "CIR") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(T = T, 
                      N = N, X0 = X0, delta = delta, method = "milstein", 
                      theta = c(phi[j], drift.param[index[j], 
                        3], sig), sigma.x = expression(sig/(2 * 
                        sqrt(x))), sigma = expression(sig * sqrt(x)), 
                      model = "CIR"))
                  }
                }
            }
            if (nb.mixt == 1) {
                phi <- drift.param[1] + drift.param[2] * rnorm(M, 
                  mean = 0, sd = 1)
                if (model == "OU") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(T = T, 
                      X0 = X0, N = N, delta = delta, method = "EA", 
                      theta = c(phi[j], drift.param[3], sig), 
                      model = "OU"))
                  }
                }
                if (model == "CIR") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(T = T, 
                      N = N, X0 = X0, delta = delta, method = "milstein", 
                      theta = c(phi[j], drift.param[3], sig), 
                      sigma.x = expression(sig/(2 * sqrt(x))), 
                      sigma = expression(sig * sqrt(x)), model = "CIR"))
                  }
                }
            }
        }
        if (sum(drift.random) == 2) {
            phi <- rep(0, M)
            if (nb.mixt > 1) {
                sim <- mixture.sim(M, drift.param[, c(2, 3)], 
                  mixt.prop)
                phi <- sim$Y
                index <- sim$index
                if (model == "OU") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(T = T, 
                      X0 = X0, N = N, delta = delta, method = "EA", 
                      theta = c(drift.param[index[j], 1], phi[j], 
                        sig), model = "OU"))
                  }
                }
                if (model == "CIR") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(t0, T, 
                      X0, N, delta, method = "milstein", theta = c(drift.param[index[j], 
                        1], phi[j], sig), sigma.x = expression(sig/(2 * 
                        sqrt(x))), sigma = expression(sig * sqrt(x)), 
                      model = "CIR"))
                  }
                }
            }
            if (nb.mixt == 1) {
                phi <- drift.param[2] + drift.param[3] * rnorm(M, 
                  mean = 0, sd = 1)
                if (model == "OU") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(T = T, 
                      X0 = X0, N = N, delta = delta, method = "EA", 
                      theta = c(drift.param[1], phi[j], sig), 
                      model = "OU"))
                  }
                }
                if (model == "CIR") {
                  for (j in 1:M) {
                    suppressMessages(X[j, ] <- sde.sim(t0, T, 
                      X0, N, delta, method = "milstein", theta = c(drift.param[1], 
                        phi[j], sig), sigma.x = expression(sig/(2 * 
                        sqrt(x))), sigma = expression(sig * sqrt(x)), 
                      model = "CIR"))
                  }
                }
            }
        }
    }
    if (diffusion.random == 1) {
        psi <- 1/sqrt(rgamma(M, shape = diffusion.param[1], rate = 1/diffusion.param[2]))
        if ((sum(drift.random) > 2)) {
            phi <- matrix(0, 2, M)
            if (nb.mixt == 1) {
                for (j in 1:M) {
                  phi[1, j] <- rnorm(1, drift.param[1], sd = drift.param[2] * 
                    psi[j])
                  phi[2, j] <- rnorm(1, drift.param[3], sd = drift.param[4] * 
                    psi[j])
                }
            }
            if (model == "OU") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(T = T, X0 = X0, 
                    N = N, delta = delta, method = "EA", theta = c(phi[, 
                      j], psi[j]), model = "OU"))
                }
            }
            if (model == "CIR") {
                message("to consider a random effect in the diffusion coefficient, alphaj should not be random")
            }
        }
        if (sum(drift.random) == 1) {
            phi <- rep(0, M)
            if (nb.mixt == 1) {
                for (j in 1:M) {
                  phi[j] <- drift.param[1] + drift.param[2] * 
                    psi[j] * rnorm(1, mean = 0, sd = 1)
                }
            }
            if (model == "OU") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(T = T, X0 = X0, 
                    N = N, delta = delta, method = "EA", theta = c(phi[j], 
                      drift.param[3], psi[j]), model = "OU"))
                }
            }
            if (model == "CIR") {
                message("to consider a random effect in the diffusion coefficient, alphaj should not be random")
            }
        }
        if (sum(drift.random) == 2) {
            phi <- rep(0, M)
            if (nb.mixt == 1) {
                for (j in 1:M) {
                  phi[j] <- drift.param[2] + drift.param[3] * 
                    psi[j] * rnorm(1, mean = 0, sd = 1)
                }
            }
            if (model == "OU") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(T = T, X0 = X0, 
                    N = N, delta = delta, method = "EA", theta = c(drift.param[1], 
                      phi[j], psi[j]), model = "OU"))
                }
            }
            if (model == "CIR") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(t0, T, X0, 
                    N, delta, method = "milstein", theta = c(drift.param[1], 
                      phi[j], psi[j]), sigma.x = expression(psi[j]/(2 * 
                      sqrt(x))), sigma = expression(psi[j] * 
                      sqrt(x)), model = "CIR"))
                }
            }
        }
        if (sum(drift.random) == 0) {
            phi <- NA
            if (model == "OU") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(T = T, X0 = X0, 
                    N = N, delta = delta, method = "EA", theta = c(drift.param[1], 
                      drift.param[2], psi[j]), model = "OU"))
                }
            }
            if (model == "CIR") {
                for (j in 1:M) {
                  suppressMessages(X[j, ] <- sde.sim(t0, T, X0, 
                    N, delta, method = "milstein", theta = c(drift.param[1], 
                      drift.param[2], psi[j]), sigma.x = expression(psi[j]/(2 * 
                      sqrt(x))), sigma = expression(psi[j] * 
                      sqrt(x)), model = "CIR"))
                }
            }
        }
    }
    output <- X
    if (op.plot) {
        if (add.plot) {
            for (j in 1:M) {
                lines(delta * (0:N), X[j, ], col = j)
            }
        }
        else {
            plot(delta * (0:N), X[1, ], type = "l", ylim = c(min(X), 
                max(X)), xlab = "time", ylab = "", col = 1)
            for (j in 2:M) {
                lines(delta * (0:N), X[j, ], col = j)
            }
        }
    }
    return(list(index = index, phi = phi, psi = psi, X = X, times = times))
}
<bytecode: 0xb9f5878>
<environment: namespace:MsdeParEst>
 --- function search by body ---
Function msde.sim in namespace MsdeParEst has this body.
 ----------- END OF FAILURE REPORT -------------- 
Fatal error: length > 1 in coercion to logical
* checking PDF version of manual ... OK
* checking for non-standard things in the check directory ... OK
* checking for detritus in the temp directory ... OK
* DONE

Status: 1 ERROR, 1 NOTE
See
  ‘/data/gannet/ripley/R/packages/tests-LENGTH1/MsdeParEst.Rcheck/00check.log’
for details.

Command exited with non-zero status 1
Time 3:44.07, 119.80 + 11.79