CRAN Package Check Results for Package MARSS

Last updated on 2018-06-22 10:50:31 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 3.10.8 13.59 132.92 146.51 ERROR
r-devel-linux-x86_64-debian-gcc 3.10.8 11.67 111.33 123.00 ERROR
r-devel-linux-x86_64-fedora-clang 3.10.8 202.50 OK
r-devel-linux-x86_64-fedora-gcc 3.10.8 197.67 OK
r-devel-windows-ix86+x86_64 3.10.8 23.00 137.00 160.00 OK
r-patched-linux-x86_64 3.10.8 12.77 143.46 156.23 ERROR
r-patched-solaris-x86 3.10.8 205.70 OK
r-release-linux-x86_64 3.10.8 14.19 143.92 158.11 ERROR
r-release-windows-ix86+x86_64 3.10.8 17.00 147.00 164.00 OK
r-release-osx-x86_64 3.10.8 OK
r-oldrel-windows-ix86+x86_64 3.10.8 24.00 149.00 173.00 OK
r-oldrel-osx-x86_64 3.10.8 OK

Check Details

Version: 3.10.8
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: augment doesn't know how to deal with data of class marssMLE
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64