CRAN Package Check Results for Package CompRandFld

Last updated on 2016-09-30 04:48:55.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.3-4 6.31 28.39 34.70 ERROR
r-devel-linux-x86_64-debian-gcc 1.0.3-4 7.29 29.38 36.67 ERROR
r-devel-linux-x86_64-fedora-clang 1.0.3-4 68.86 ERROR
r-devel-linux-x86_64-fedora-gcc 1.0.3-4 57.54 ERROR
r-devel-macos-x86_64-clang 1.0.3-4 43.84 ERROR
r-devel-windows-ix86+x86_64 1.0.3-4 27.00 67.00 94.00 ERROR
r-patched-linux-x86_64 1.0.3-4 6.74 27.36 34.09 ERROR
r-patched-solaris-sparc 1.0.3-4 303.70 ERROR
r-patched-solaris-x86 1.0.3-4 60.00 ERROR
r-release-linux-x86_64 1.0.3-4 6.87 28.00 34.86 ERROR
r-release-osx-x86_64-mavericks 1.0.3-4 NOTE
r-release-windows-ix86+x86_64 1.0.3-4 26.00 55.00 81.00 ERROR
r-oldrel-windows-ix86+x86_64 1.0.3-4 44.00 70.00 114.00 ERROR

Check Details

Version: 1.0.3-4
Check: R code for possible problems
Result: NOTE
    CompLikelihood: no visible global function definition for ‘optim’
    Covariogram: no visible global function definition for ‘uniroot’
    Covariogram: no visible global function definition for ‘pnorm’
    Covariogram: no visible global function definition for ‘par’
    Covariogram: no visible global function definition for ‘persp’
    Covariogram: no visible global function definition for ‘plot’
    Covariogram: no visible global function definition for ‘dev.cur’
    Covariogram: no visible global function definition for ‘lines’
    Covariogram: no visible global function definition for ‘abline’
    Covariogram: no visible global function definition for ‘points’
    Covmatrix : Cmatrix: no visible global function definition for ‘new’
    FitGev: no visible global function definition for ‘optim’
    HypoTest: no visible global function definition for ‘pchisq’
    InitParam: no visible global function definition for ‘var’
    InitParam: no visible global function definition for ‘qnorm’
    Kri: no visible global function definition for ‘window’
    Likelihood : LogNormDenTap: no visible global function definition for
     ‘new’
    Likelihood : LogNormDenTap: no visible global function definition for
     ‘slot<-’
    Likelihood: no visible global function definition for ‘optim’
    Likelihood: no visible global function definition for ‘new’
    Likelihood: no visible global function definition for ‘slot<-’
    MomEst: no visible global function definition for ‘var’
    RFsim : CholRFsim: no visible global function definition for ‘rnorm’
    WLeastSquare: no visible global function definition for ‘optim’
    WlsInit: no visible global function definition for ‘optim’
    Undefined global functions or variables:
     abline dev.cur lines new optim par pchisq persp plot pnorm points
     qnorm rnorm slot<- uniroot var window
    Consider adding
     importFrom("grDevices", "dev.cur")
     importFrom("graphics", "abline", "lines", "par", "persp", "plot",
     "points")
     importFrom("methods", "new", "slot<-")
     importFrom("stats", "optim", "pchisq", "pnorm", "qnorm", "rnorm",
     "uniroot", "var", "window")
    to your NAMESPACE file (and ensure that your DESCRIPTION Imports field
    contains 'methods').
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-macos-x86_64-clang, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-sparc, r-patched-solaris-x86, r-release-linux-x86_64, r-release-osx-x86_64-mavericks, r-release-windows-ix86+x86_64

Version: 1.0.3-4
Check: examples
Result: ERROR
    Running examples in ‘CompRandFld-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: EVariogram
    > ### Title: Empirical Variogram(variants) of Gaussian, Binary and Max-Stable
    > ### Fields
    > ### Aliases: EVariogram
    > ### Keywords: Variogram
    >
    > ### ** Examples
    >
    > library(CompRandFld)
    > library(RandomFields)
    Loading required package: sp
    Loading required package: RandomFieldsUtils
    This is RandomFieldsUtils Version: 0.3.3
    This is RandomFields Version: 3.1.24
    
    Attaching package: ‘RandomFields’
    
    The following object is masked from ‘package:RandomFieldsUtils’:
    
     RFoptions
    
    The following objects are masked from ‘package:base’:
    
     abs, acosh, asin, asinh, atan, atan2, atanh, cos, cosh, exp, expm1,
     floor, gamma, lgamma, log, log1p, log2, logb, max, min, round, sin,
     sinh, sqrt, tan, tanh, trunc
    
    > set.seed(514)
    >
    > # Set the coordinates of the sites:
    > x <- runif(150, 0, 10)
    > y <- runif(150, 0, 10)
    >
    >
    > ################################################################
    > ###
    > ### Example 1. Empirical estimation of the variogram from a
    > ### Gaussian random field with exponential correlation.
    > ### One spatial replication is simulated.
    > ###
    > ###
    > ###############################################################
    >
    > # Set the model's parameters:
    > corrmodel <- "exponential"
    > mean <- 0
    > sill <- 1
    > nugget <- 0
    > scale <- 3
    >
    > # Simulation of the spatial Gaussian random field:
    > data <- RFsim(x, y, corrmodel=corrmodel, param=list(mean=mean,
    + sill=sill, nugget=nugget, scale=scale))$data
    >
    > # Empirical spatial variogram estimation:
    > fit <- EVariogram(data, x, y)
    >
    > # Results:
    > plot(fit$centers, fit$variograms, xlab='h', ylab=expression(gamma(h)),
    + ylim=c(0, max(fit$variograms)), xlim=c(0, fit$srange[2]), pch=20,
    + main="variogram")
    >
    >
    > ################################################################
    > ###
    > ### Example 2. Empirical estimation of the variogram from a
    > ### spatio-temporal Gaussian random fields with Gneiting
    > ### correlation function.
    > ### One spatio-temporal replication is simulated
    > ###
    > ###############################################################
    >
    > set.seed(331)
    > # Define the temporal sequence:
    > times <- seq(1,7,1)
    >
    > # Simulation of a spatio-temporal Gaussian random field:
    > data <- RFsim(x, y, times, corrmodel="gneiting",
    + param=list(mean=0,scale_s=0.4,scale_t=1,sill=sill,
    + nugget=0,power_s=1,power_t=1,sep=0.5))$data
    >
    > # Empirical spatio-temporal variogram estimation:
    > fit <- EVariogram(data, x, y, times, maxtime=5,maxdist=4)
    >
    > # Results: Marginal spatial empirical variogram
    > par(mfrow=c(2,2), mai=c(.5,.5,.3,.3), mgp=c(1.4,.5, 0))
    > plot(fit$centers, fit$variograms, xlab='h', ylab=expression(gamma(h)),
    + ylim=c(0, max(fit$variograms)), xlim=c(0, max(fit$centers)),
    + pch=20,main="Marginal spatial Variogram",cex.axis=.8)
    >
    > # Results: Marginal temporal empirical variogram
    > plot(fit$bint, fit$variogramt, xlab='t', ylab=expression(gamma(t)),
    + ylim=c(0, max(fit$variograms)),xlim=c(0,max(fit$bint)),
    + pch=20,main="Marginal temporal Variogram",cex.axis=.8)
    >
    > # Building space-time variogram
    > st.vario <- matrix(fit$variogramst,length(fit$centers),length(fit$bint))
    > st.vario <- cbind(c(0,fit$variograms), rbind(fit$variogramt,st.vario))
    >
    > # Results: 3d Spatio-temporal variogram
    > require(scatterplot3d)
    Loading required package: scatterplot3d
    > st.grid <- expand.grid(c(0,fit$centers),c(0,fit$bint))
    > scatterplot3d(st.grid[,1], st.grid[,2], c(st.vario),
    + highlight.3d=TRUE, xlab="h",ylab="t",
    + zlab=expression(gamma(h,t)), pch=20,
    + main="Space-time variogram",cex.axis=.7,
    + mar=c(2,2,2,2), mgp=c(0,0,0),
    + cex.lab=.7)
    >
    > # A smoothed version
    > par(mai=c(.2,.2,.2,.2),mgp=c(1,.3, 0))
    > persp(c(0,fit$centers), c(0,fit$bint), st.vario,
    + xlab="h", ylab="u", zlab=expression(gamma(h,u)),
    + ltheta=90, shade=0.75, ticktype="detailed", phi=30,
    + theta=30,main="Space-time variogram",cex.axis=.8,
    + cex.lab=.8)
    >
    >
    > ################################################################
    > ###
    > ### Example 3. Empirical estimation of the madogram from a
    > ### max-stable random field (Extremal Gaussian model) with
    > ### exponential correlation.
    > ### n iid spatial replications are simulated.
    > ###
    > ###############################################################
    >
    > set.seed(7273)
    > # Simulation of the max-stable random field:
    > data <- RFsim(x, y, corrmodel=corrmodel, model="ExtGauss",
    + param=list(mean=mean, sill=sill, nugget=nugget,
    + scale=scale), replicates=40)$data
    Error in lapply(.External(C_RFoptions, ...), function(x) { :
     Unknown option 'asList'.
    Calls: RFsim ... internal.rfoptions -> <Anonymous> -> lapply -> .External
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-macos-x86_64-clang, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 1.0.3-4
Check: running examples for arch ‘i386’
Result: ERROR
    Running examples in 'CompRandFld-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: EVariogram
    > ### Title: Empirical Variogram(variants) of Gaussian, Binary and Max-Stable
    > ### Fields
    > ### Aliases: EVariogram
    > ### Keywords: Variogram
    >
    > ### ** Examples
    >
    > library(CompRandFld)
    > library(RandomFields)
    Loading required package: sp
    Loading required package: RandomFieldsUtils
    This is RandomFieldsUtils Version: 0.3.3
    This is RandomFields Version: 3.1.24
    
    Attaching package: 'RandomFields'
    
    The following object is masked from 'package:RandomFieldsUtils':
    
     RFoptions
    
    The following objects are masked from 'package:base':
    
     abs, acosh, asin, asinh, atan, atan2, atanh, cos, cosh, exp, expm1,
     floor, gamma, lgamma, log, log1p, log2, logb, max, min, round, sin,
     sinh, sqrt, tan, tanh, trunc
    
    > set.seed(514)
    >
    > # Set the coordinates of the sites:
    > x <- runif(150, 0, 10)
    > y <- runif(150, 0, 10)
    >
    >
    > ################################################################
    > ###
    > ### Example 1. Empirical estimation of the variogram from a
    > ### Gaussian random field with exponential correlation.
    > ### One spatial replication is simulated.
    > ###
    > ###
    > ###############################################################
    >
    > # Set the model's parameters:
    > corrmodel <- "exponential"
    > mean <- 0
    > sill <- 1
    > nugget <- 0
    > scale <- 3
    >
    > # Simulation of the spatial Gaussian random field:
    > data <- RFsim(x, y, corrmodel=corrmodel, param=list(mean=mean,
    + sill=sill, nugget=nugget, scale=scale))$data
    >
    > # Empirical spatial variogram estimation:
    > fit <- EVariogram(data, x, y)
    >
    > # Results:
    > plot(fit$centers, fit$variograms, xlab='h', ylab=expression(gamma(h)),
    + ylim=c(0, max(fit$variograms)), xlim=c(0, fit$srange[2]), pch=20,
    + main="variogram")
    >
    >
    > ################################################################
    > ###
    > ### Example 2. Empirical estimation of the variogram from a
    > ### spatio-temporal Gaussian random fields with Gneiting
    > ### correlation function.
    > ### One spatio-temporal replication is simulated
    > ###
    > ###############################################################
    >
    > set.seed(331)
    > # Define the temporal sequence:
    > times <- seq(1,7,1)
    >
    > # Simulation of a spatio-temporal Gaussian random field:
    > data <- RFsim(x, y, times, corrmodel="gneiting",
    + param=list(mean=0,scale_s=0.4,scale_t=1,sill=sill,
    + nugget=0,power_s=1,power_t=1,sep=0.5))$data
    >
    > # Empirical spatio-temporal variogram estimation:
    > fit <- EVariogram(data, x, y, times, maxtime=5,maxdist=4)
    >
    > # Results: Marginal spatial empirical variogram
    > par(mfrow=c(2,2), mai=c(.5,.5,.3,.3), mgp=c(1.4,.5, 0))
    > plot(fit$centers, fit$variograms, xlab='h', ylab=expression(gamma(h)),
    + ylim=c(0, max(fit$variograms)), xlim=c(0, max(fit$centers)),
    + pch=20,main="Marginal spatial Variogram",cex.axis=.8)
    >
    > # Results: Marginal temporal empirical variogram
    > plot(fit$bint, fit$variogramt, xlab='t', ylab=expression(gamma(t)),
    + ylim=c(0, max(fit$variograms)),xlim=c(0,max(fit$bint)),
    + pch=20,main="Marginal temporal Variogram",cex.axis=.8)
    >
    > # Building space-time variogram
    > st.vario <- matrix(fit$variogramst,length(fit$centers),length(fit$bint))
    > st.vario <- cbind(c(0,fit$variograms), rbind(fit$variogramt,st.vario))
    >
    > # Results: 3d Spatio-temporal variogram
    > require(scatterplot3d)
    Loading required package: scatterplot3d
    > st.grid <- expand.grid(c(0,fit$centers),c(0,fit$bint))
    > scatterplot3d(st.grid[,1], st.grid[,2], c(st.vario),
    + highlight.3d=TRUE, xlab="h",ylab="t",
    + zlab=expression(gamma(h,t)), pch=20,
    + main="Space-time variogram",cex.axis=.7,
    + mar=c(2,2,2,2), mgp=c(0,0,0),
    + cex.lab=.7)
    >
    > # A smoothed version
    > par(mai=c(.2,.2,.2,.2),mgp=c(1,.3, 0))
    > persp(c(0,fit$centers), c(0,fit$bint), st.vario,
    + xlab="h", ylab="u", zlab=expression(gamma(h,u)),
    + ltheta=90, shade=0.75, ticktype="detailed", phi=30,
    + theta=30,main="Space-time variogram",cex.axis=.8,
    + cex.lab=.8)
    >
    >
    > ################################################################
    > ###
    > ### Example 3. Empirical estimation of the madogram from a
    > ### max-stable random field (Extremal Gaussian model) with
    > ### exponential correlation.
    > ### n iid spatial replications are simulated.
    > ###
    > ###############################################################
    >
    > set.seed(7273)
    > # Simulation of the max-stable random field:
    > data <- RFsim(x, y, corrmodel=corrmodel, model="ExtGauss",
    + param=list(mean=mean, sill=sill, nugget=nugget,
    + scale=scale), replicates=40)$data
    Error in lapply(.External(C_RFoptions, ...), function(x) { :
     Unknown option 'asList'.
    Calls: RFsim ... internal.rfoptions -> <Anonymous> -> lapply -> .External
    Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 1.0.3-4
Check: running examples for arch ‘x64’
Result: ERROR
    Running examples in 'CompRandFld-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: EVariogram
    > ### Title: Empirical Variogram(variants) of Gaussian, Binary and Max-Stable
    > ### Fields
    > ### Aliases: EVariogram
    > ### Keywords: Variogram
    >
    > ### ** Examples
    >
    > library(CompRandFld)
    > library(RandomFields)
    Loading required package: sp
    Loading required package: RandomFieldsUtils
    This is RandomFieldsUtils Version: 0.3.3
    This is RandomFields Version: 3.1.24
    
    Attaching package: 'RandomFields'
    
    The following object is masked from 'package:RandomFieldsUtils':
    
     RFoptions
    
    The following objects are masked from 'package:base':
    
     abs, acosh, asin, asinh, atan, atan2, atanh, cos, cosh, exp, expm1,
     floor, gamma, lgamma, log, log1p, log2, logb, max, min, round, sin,
     sinh, sqrt, tan, tanh, trunc
    
    > set.seed(514)
    >
    > # Set the coordinates of the sites:
    > x <- runif(150, 0, 10)
    > y <- runif(150, 0, 10)
    >
    >
    > ################################################################
    > ###
    > ### Example 1. Empirical estimation of the variogram from a
    > ### Gaussian random field with exponential correlation.
    > ### One spatial replication is simulated.
    > ###
    > ###
    > ###############################################################
    >
    > # Set the model's parameters:
    > corrmodel <- "exponential"
    > mean <- 0
    > sill <- 1
    > nugget <- 0
    > scale <- 3
    >
    > # Simulation of the spatial Gaussian random field:
    > data <- RFsim(x, y, corrmodel=corrmodel, param=list(mean=mean,
    + sill=sill, nugget=nugget, scale=scale))$data
    >
    > # Empirical spatial variogram estimation:
    > fit <- EVariogram(data, x, y)
    >
    > # Results:
    > plot(fit$centers, fit$variograms, xlab='h', ylab=expression(gamma(h)),
    + ylim=c(0, max(fit$variograms)), xlim=c(0, fit$srange[2]), pch=20,
    + main="variogram")
    >
    >
    > ################################################################
    > ###
    > ### Example 2. Empirical estimation of the variogram from a
    > ### spatio-temporal Gaussian random fields with Gneiting
    > ### correlation function.
    > ### One spatio-temporal replication is simulated
    > ###
    > ###############################################################
    >
    > set.seed(331)
    > # Define the temporal sequence:
    > times <- seq(1,7,1)
    >
    > # Simulation of a spatio-temporal Gaussian random field:
    > data <- RFsim(x, y, times, corrmodel="gneiting",
    + param=list(mean=0,scale_s=0.4,scale_t=1,sill=sill,
    + nugget=0,power_s=1,power_t=1,sep=0.5))$data
    >
    > # Empirical spatio-temporal variogram estimation:
    > fit <- EVariogram(data, x, y, times, maxtime=5,maxdist=4)
    >
    > # Results: Marginal spatial empirical variogram
    > par(mfrow=c(2,2), mai=c(.5,.5,.3,.3), mgp=c(1.4,.5, 0))
    > plot(fit$centers, fit$variograms, xlab='h', ylab=expression(gamma(h)),
    + ylim=c(0, max(fit$variograms)), xlim=c(0, max(fit$centers)),
    + pch=20,main="Marginal spatial Variogram",cex.axis=.8)
    >
    > # Results: Marginal temporal empirical variogram
    > plot(fit$bint, fit$variogramt, xlab='t', ylab=expression(gamma(t)),
    + ylim=c(0, max(fit$variograms)),xlim=c(0,max(fit$bint)),
    + pch=20,main="Marginal temporal Variogram",cex.axis=.8)
    >
    > # Building space-time variogram
    > st.vario <- matrix(fit$variogramst,length(fit$centers),length(fit$bint))
    > st.vario <- cbind(c(0,fit$variograms), rbind(fit$variogramt,st.vario))
    >
    > # Results: 3d Spatio-temporal variogram
    > require(scatterplot3d)
    Loading required package: scatterplot3d
    > st.grid <- expand.grid(c(0,fit$centers),c(0,fit$bint))
    > scatterplot3d(st.grid[,1], st.grid[,2], c(st.vario),
    + highlight.3d=TRUE, xlab="h",ylab="t",
    + zlab=expression(gamma(h,t)), pch=20,
    + main="Space-time variogram",cex.axis=.7,
    + mar=c(2,2,2,2), mgp=c(0,0,0),
    + cex.lab=.7)
    >
    > # A smoothed version
    > par(mai=c(.2,.2,.2,.2),mgp=c(1,.3, 0))
    > persp(c(0,fit$centers), c(0,fit$bint), st.vario,
    + xlab="h", ylab="u", zlab=expression(gamma(h,u)),
    + ltheta=90, shade=0.75, ticktype="detailed", phi=30,
    + theta=30,main="Space-time variogram",cex.axis=.8,
    + cex.lab=.8)
    >
    >
    > ################################################################
    > ###
    > ### Example 3. Empirical estimation of the madogram from a
    > ### max-stable random field (Extremal Gaussian model) with
    > ### exponential correlation.
    > ### n iid spatial replications are simulated.
    > ###
    > ###############################################################
    >
    > set.seed(7273)
    > # Simulation of the max-stable random field:
    > data <- RFsim(x, y, corrmodel=corrmodel, model="ExtGauss",
    + param=list(mean=mean, sill=sill, nugget=nugget,
    + scale=scale), replicates=40)$data
    Error in lapply(.External(C_RFoptions, ...), function(x) { :
     Unknown option 'asList'.
    Calls: RFsim ... internal.rfoptions -> <Anonymous> -> lapply -> .External
    Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 1.0.3-4
Check: package dependencies
Result: NOTE
    Package suggested but not available for checking: ‘RandomFields’
Flavors: r-patched-solaris-sparc, r-patched-solaris-x86

Version: 1.0.3-4
Check: Rd cross-references
Result: NOTE
    Package unavailable to check Rd xrefs: ‘RandomFields’
Flavors: r-patched-solaris-sparc, r-patched-solaris-x86

Version: 1.0.3-4
Check: examples
Result: ERROR
    Running examples in ‘CompRandFld-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: Covariogram
    > ### Title: Computes covariance, variogram and extremal coefficient
    > ### functions
    > ### Aliases: Covariogram
    > ### Keywords: Composite
    >
    > ### ** Examples
    >
    > library(CompRandFld)
    > library(RandomFields)
    Error in library(RandomFields) :
     there is no package called ‘RandomFields’
    Execution halted
Flavors: r-patched-solaris-sparc, r-patched-solaris-x86