CRAN Package Check Results for Package MARSS

Last updated on 2019-04-19 21:46:53 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 3.10.10 17.13 160.54 177.67 OK
r-devel-linux-x86_64-debian-gcc 3.10.10 13.61 123.05 136.66 OK
r-devel-linux-x86_64-fedora-clang 3.10.10 204.61 OK
r-devel-linux-x86_64-fedora-gcc 3.10.10 200.41 OK
r-devel-windows-ix86+x86_64 3.10.10 30.00 227.00 257.00 OK
r-patched-linux-x86_64 3.10.10 15.82 159.45 175.27 OK
r-patched-solaris-x86 3.10.10 225.00 OK
r-release-linux-x86_64 3.10.10 11.33 145.12 156.45 ERROR
r-release-windows-ix86+x86_64 3.10.10 17.00 154.00 171.00 OK
r-release-osx-x86_64 3.10.10 OK
r-oldrel-windows-ix86+x86_64 3.10.10 16.00 203.00 219.00 OK
r-oldrel-osx-x86_64 3.10.10 OK

Check Details

Version: 3.10.10
Check: examples
Result: ERROR
    Running examples in ‘MARSS-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: augment.marssMLE
    > ### Title: Return the model predicted values, residuals, and optionally
    > ### confidence intervals
    > ### Aliases: augment.marssMLE augment_dfa augment_marss augmentmarxss
    >
    > ### ** Examples
    >
    > dat <- t(harborSeal)
    > dat <- dat[c(2,11,12),]
    > MLEobj <- MARSS(dat, model=list(Z=factor(c("WA","OR","OR"))))
    Success! abstol and log-log tests passed at 37 iterations.
    Alert: conv.test.slope.tol is 0.5.
    Test with smaller values (<0.1) to ensure convergence.
    
    MARSS fit is
    Estimation method: kem
    Convergence test: conv.test.slope.tol = 0.5, abstol = 0.001
    Estimation converged in 37 iterations.
    Log-likelihood: 13.72233
    AIC: -11.44465 AICc: -8.918339
    
     Estimate
    A.OR.SouthCoast 0.49280
    R.diag 0.02509
    U.WA 0.06171
    U.OR 0.03686
    Q.(WA,WA) 0.01082
    Q.(OR,OR) 0.00439
    x0.WA 7.41712
    x0.OR 6.56460
    Initial states (x0) defined at t=0
    
    Standard errors have not been calculated.
    Use MARSSparamCIs to compute CIs and bias estimates.
    
    >
    > library(broom)
    > library(ggplot2)
    > theme_set(theme_bw())
    >
    > # Make a plot of the observations and model fits
    > d <- augment(MLEobj, interval="confidence")
    Error: No augment method for objects of class marssMLE
    Execution halted
Flavor: r-release-linux-x86_64