CRAN Package Check Results for Package frailtySurv

Last updated on 2019-03-25 06:47:08 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.3.5 36.15 78.36 114.51 ERROR
r-devel-linux-x86_64-debian-gcc 1.3.5 29.24 62.59 91.83 ERROR
r-devel-linux-x86_64-fedora-clang 1.3.5 158.04 ERROR
r-devel-linux-x86_64-fedora-gcc 1.3.5 140.72 ERROR
r-devel-windows-ix86+x86_64 1.3.5 95.00 167.00 262.00 ERROR
r-patched-linux-x86_64 1.3.5 31.65 75.93 107.58 OK
r-patched-solaris-x86 1.3.5 173.20 OK
r-release-linux-x86_64 1.3.5 31.78 75.55 107.33 OK
r-release-windows-ix86+x86_64 1.3.5 68.00 130.00 198.00 OK
r-release-osx-x86_64 1.3.5 OK
r-oldrel-windows-ix86+x86_64 1.3.5 66.00 142.00 208.00 OK
r-oldrel-osx-x86_64 1.3.5 OK

Check Details

Version: 1.3.5
Check: examples
Result: ERROR
    Running examples in 'frailtySurv-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: genfrail
    > ### Title: Generate survival data
    > ### Aliases: genfrail
    > ### Keywords: survival data shared frailty
    >
    > ### ** Examples
    >
    > # Generate the same dataset 3 different ways
    >
    > # Using the baseline hazard (least efficient)
    > set.seed(1234)
    > dat.1 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + lambda_0=function(t, tau=4.6, C=0.01) (tau*(C*t)^tau)/t)
    >
    > # Using the cumulative baseline hazard
    > set.seed(1234)
    > dat.2 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0 = function(t, tau=4.6, C=0.01) (C*t)^tau)
    >
    > # Using the inverse cumulative baseline hazard (most efficient)
    > set.seed(1234)
    > dat.3 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    >
    > # Generate data with PVF frailty, truncated Poisson cluster sizes, normal
    > # covariates, and 0.35 censorship from a lognormal distribution
    > dat.4 <- genfrail(N = 100, K = "poisson", K.param=c(5, 1),
    + beta = c(log(2),log(3)),
    + frailty = "pvf", theta = 0.3,
    + covar.distr = "lognormal",
    + censor.rate = 0.35) # Use the default baseline hazard
    Warning in genfrail(N = 100, K = "poisson", K.param = c(5, 1), beta = c(log(2), :
     Using a default baseline hazard. Did you forget to pass Lambda_0?
    >
    > # Cluster sizes have size >= 2, summarized by
    > summary(dat.4)
    genfrail created : 2019-03-24 21:22:16
    Observations : 543
    Clusters : 100
    Avg. cluster size : 5.43
    Right censoring rate : 0.34
    Covariates : lognormal(0, 1)
    Coefficients : 0.6931, 1.0986
    Frailty : pvf(0.3)
    Baseline hazard : (default) Lambda_0
     = function (t, c = 0.01, d = 4.6) (c * t)^d
    >
    > # An oscillating baseline hazard
    > dat.5 <- genfrail(lambda_0=function(t, tau=4.6, C=0.01, A=2, f=0.1)
    + A^sin(f*pi*t) * (tau*(C*t)^tau)/t)
    >
    > # Uniform censorship with 0.25 censoring rate
    > dat.6 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + censor.distr = "uniform",
    + censor.param = c(50, 150),
    + censor.rate = 0.25,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    Error in integrate(function(t) efail(t) * censor.density(t, lower, upper), :
     roundoff error was detected
    Calls: genfrail -> uniroot -> f -> integrate
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 1.3.5
Check: examples
Result: ERROR
    Running examples in ‘frailtySurv-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: genfrail
    > ### Title: Generate survival data
    > ### Aliases: genfrail
    > ### Keywords: survival data shared frailty
    >
    > ### ** Examples
    >
    > # Generate the same dataset 3 different ways
    >
    > # Using the baseline hazard (least efficient)
    > set.seed(1234)
    > dat.1 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + lambda_0=function(t, tau=4.6, C=0.01) (tau*(C*t)^tau)/t)
    >
    > # Using the cumulative baseline hazard
    > set.seed(1234)
    > dat.2 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0 = function(t, tau=4.6, C=0.01) (C*t)^tau)
    >
    > # Using the inverse cumulative baseline hazard (most efficient)
    > set.seed(1234)
    > dat.3 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    >
    > # Generate data with PVF frailty, truncated Poisson cluster sizes, normal
    > # covariates, and 0.35 censorship from a lognormal distribution
    > dat.4 <- genfrail(N = 100, K = "poisson", K.param=c(5, 1),
    + beta = c(log(2),log(3)),
    + frailty = "pvf", theta = 0.3,
    + covar.distr = "lognormal",
    + censor.rate = 0.35) # Use the default baseline hazard
    Warning in genfrail(N = 100, K = "poisson", K.param = c(5, 1), beta = c(log(2), :
     Using a default baseline hazard. Did you forget to pass Lambda_0?
    >
    > # Cluster sizes have size >= 2, summarized by
    > summary(dat.4)
    genfrail created : 2019-03-24 19:49:25
    Observations : 543
    Clusters : 100
    Avg. cluster size : 5.43
    Right censoring rate : 0.34
    Covariates : lognormal(0, 1)
    Coefficients : 0.6931, 1.0986
    Frailty : pvf(0.3)
    Baseline hazard : (default) Lambda_0
     = function (t, c = 0.01, d = 4.6) (c * t)^d
    >
    > # An oscillating baseline hazard
    > dat.5 <- genfrail(lambda_0=function(t, tau=4.6, C=0.01, A=2, f=0.1)
    + A^sin(f*pi*t) * (tau*(C*t)^tau)/t)
    >
    > # Uniform censorship with 0.25 censoring rate
    > dat.6 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + censor.distr = "uniform",
    + censor.param = c(50, 150),
    + censor.rate = 0.25,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    Error in integrate(function(t) efail(t) * censor.density(t, lower, upper), :
     roundoff error was detected
    Calls: genfrail -> uniroot -> f -> integrate
    Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 1.3.5
Check: examples
Result: ERROR
    Running examples in ‘frailtySurv-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: genfrail
    > ### Title: Generate survival data
    > ### Aliases: genfrail
    > ### Keywords: survival data shared frailty
    >
    > ### ** Examples
    >
    > # Generate the same dataset 3 different ways
    >
    > # Using the baseline hazard (least efficient)
    > set.seed(1234)
    > dat.1 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + lambda_0=function(t, tau=4.6, C=0.01) (tau*(C*t)^tau)/t)
    >
    > # Using the cumulative baseline hazard
    > set.seed(1234)
    > dat.2 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0 = function(t, tau=4.6, C=0.01) (C*t)^tau)
    >
    > # Using the inverse cumulative baseline hazard (most efficient)
    > set.seed(1234)
    > dat.3 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    >
    > # Generate data with PVF frailty, truncated Poisson cluster sizes, normal
    > # covariates, and 0.35 censorship from a lognormal distribution
    > dat.4 <- genfrail(N = 100, K = "poisson", K.param=c(5, 1),
    + beta = c(log(2),log(3)),
    + frailty = "pvf", theta = 0.3,
    + covar.distr = "lognormal",
    + censor.rate = 0.35) # Use the default baseline hazard
    Warning in genfrail(N = 100, K = "poisson", K.param = c(5, 1), beta = c(log(2), :
     Using a default baseline hazard. Did you forget to pass Lambda_0?
    >
    > # Cluster sizes have size >= 2, summarized by
    > summary(dat.4)
    genfrail created : 2019-03-23 20:08:39
    Observations : 543
    Clusters : 100
    Avg. cluster size : 5.43
    Right censoring rate : 0.34
    Covariates : lognormal(0, 1)
    Coefficients : 0.6931, 1.0986
    Frailty : pvf(0.3)
    Baseline hazard : (default) Lambda_0
     = function (t, c = 0.01, d = 4.6) (c * t)^d
    >
    > # An oscillating baseline hazard
    > dat.5 <- genfrail(lambda_0=function(t, tau=4.6, C=0.01, A=2, f=0.1)
    + A^sin(f*pi*t) * (tau*(C*t)^tau)/t)
    >
    > # Uniform censorship with 0.25 censoring rate
    > dat.6 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + censor.distr = "uniform",
    + censor.param = c(50, 150),
    + censor.rate = 0.25,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    Error in integrate(function(t) efail(t) * censor.density(t, lower, upper), :
     roundoff error was detected
    Calls: genfrail -> uniroot -> f -> integrate
    Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 1.3.5
Check: examples
Result: ERROR
    Running examples in ‘frailtySurv-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: genfrail
    > ### Title: Generate survival data
    > ### Aliases: genfrail
    > ### Keywords: survival data shared frailty
    >
    > ### ** Examples
    >
    > # Generate the same dataset 3 different ways
    >
    > # Using the baseline hazard (least efficient)
    > set.seed(1234)
    > dat.1 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + lambda_0=function(t, tau=4.6, C=0.01) (tau*(C*t)^tau)/t)
    >
    > # Using the cumulative baseline hazard
    > set.seed(1234)
    > dat.2 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0 = function(t, tau=4.6, C=0.01) (C*t)^tau)
    >
    > # Using the inverse cumulative baseline hazard (most efficient)
    > set.seed(1234)
    > dat.3 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    >
    > # Generate data with PVF frailty, truncated Poisson cluster sizes, normal
    > # covariates, and 0.35 censorship from a lognormal distribution
    > dat.4 <- genfrail(N = 100, K = "poisson", K.param=c(5, 1),
    + beta = c(log(2),log(3)),
    + frailty = "pvf", theta = 0.3,
    + covar.distr = "lognormal",
    + censor.rate = 0.35) # Use the default baseline hazard
    Warning in genfrail(N = 100, K = "poisson", K.param = c(5, 1), beta = c(log(2), :
     Using a default baseline hazard. Did you forget to pass Lambda_0?
    >
    > # Cluster sizes have size >= 2, summarized by
    > summary(dat.4)
    genfrail created : 2019-03-24 19:32:50
    Observations : 543
    Clusters : 100
    Avg. cluster size : 5.43
    Right censoring rate : 0.34
    Covariates : lognormal(0, 1)
    Coefficients : 0.6931, 1.0986
    Frailty : pvf(0.3)
    Baseline hazard : (default) Lambda_0
     = function (t, c = 0.01, d = 4.6) (c * t)^d
    >
    > # An oscillating baseline hazard
    > dat.5 <- genfrail(lambda_0=function(t, tau=4.6, C=0.01, A=2, f=0.1)
    + A^sin(f*pi*t) * (tau*(C*t)^tau)/t)
    >
    > # Uniform censorship with 0.25 censoring rate
    > dat.6 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + censor.distr = "uniform",
    + censor.param = c(50, 150),
    + censor.rate = 0.25,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    Error in integrate(function(t) efail(t) * censor.density(t, lower, upper), :
     roundoff error was detected
    Calls: genfrail -> uniroot -> f -> integrate
    Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 1.3.5
Check: running examples for arch ‘i386’
Result: ERROR
    Running examples in 'frailtySurv-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: genfrail
    > ### Title: Generate survival data
    > ### Aliases: genfrail
    > ### Keywords: survival data shared frailty
    >
    > ### ** Examples
    >
    > # Generate the same dataset 3 different ways
    >
    > # Using the baseline hazard (least efficient)
    > set.seed(1234)
    > dat.1 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + lambda_0=function(t, tau=4.6, C=0.01) (tau*(C*t)^tau)/t)
    >
    > # Using the cumulative baseline hazard
    > set.seed(1234)
    > dat.2 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0 = function(t, tau=4.6, C=0.01) (C*t)^tau)
    >
    > # Using the inverse cumulative baseline hazard (most efficient)
    > set.seed(1234)
    > dat.3 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    >
    > # Generate data with PVF frailty, truncated Poisson cluster sizes, normal
    > # covariates, and 0.35 censorship from a lognormal distribution
    > dat.4 <- genfrail(N = 100, K = "poisson", K.param=c(5, 1),
    + beta = c(log(2),log(3)),
    + frailty = "pvf", theta = 0.3,
    + covar.distr = "lognormal",
    + censor.rate = 0.35) # Use the default baseline hazard
    Warning in genfrail(N = 100, K = "poisson", K.param = c(5, 1), beta = c(log(2), :
     Using a default baseline hazard. Did you forget to pass Lambda_0?
    >
    > # Cluster sizes have size >= 2, summarized by
    > summary(dat.4)
    genfrail created : 2019-03-24 04:43:38
    Observations : 543
    Clusters : 100
    Avg. cluster size : 5.43
    Right censoring rate : 0.34
    Covariates : lognormal(0, 1)
    Coefficients : 0.6931, 1.0986
    Frailty : pvf(0.3)
    Baseline hazard : (default) Lambda_0
     = function (t, c = 0.01, d = 4.6) (c * t)^d
    >
    > # An oscillating baseline hazard
    > dat.5 <- genfrail(lambda_0=function(t, tau=4.6, C=0.01, A=2, f=0.1)
    + A^sin(f*pi*t) * (tau*(C*t)^tau)/t)
    >
    > # Uniform censorship with 0.25 censoring rate
    > dat.6 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + censor.distr = "uniform",
    + censor.param = c(50, 150),
    + censor.rate = 0.25,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    Error in integrate(function(t) efail(t) * censor.density(t, lower, upper), :
     roundoff error was detected
    Calls: genfrail -> uniroot -> f -> integrate
    Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 1.3.5
Check: running examples for arch ‘x64’
Result: ERROR
    Running examples in 'frailtySurv-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: genfrail
    > ### Title: Generate survival data
    > ### Aliases: genfrail
    > ### Keywords: survival data shared frailty
    >
    > ### ** Examples
    >
    > # Generate the same dataset 3 different ways
    >
    > # Using the baseline hazard (least efficient)
    > set.seed(1234)
    > dat.1 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + lambda_0=function(t, tau=4.6, C=0.01) (tau*(C*t)^tau)/t)
    >
    > # Using the cumulative baseline hazard
    > set.seed(1234)
    > dat.2 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0 = function(t, tau=4.6, C=0.01) (C*t)^tau)
    >
    > # Using the inverse cumulative baseline hazard (most efficient)
    > set.seed(1234)
    > dat.3 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    >
    > # Generate data with PVF frailty, truncated Poisson cluster sizes, normal
    > # covariates, and 0.35 censorship from a lognormal distribution
    > dat.4 <- genfrail(N = 100, K = "poisson", K.param=c(5, 1),
    + beta = c(log(2),log(3)),
    + frailty = "pvf", theta = 0.3,
    + covar.distr = "lognormal",
    + censor.rate = 0.35) # Use the default baseline hazard
    Warning in genfrail(N = 100, K = "poisson", K.param = c(5, 1), beta = c(log(2), :
     Using a default baseline hazard. Did you forget to pass Lambda_0?
    >
    > # Cluster sizes have size >= 2, summarized by
    > summary(dat.4)
    genfrail created : 2019-03-24 04:43:49
    Observations : 543
    Clusters : 100
    Avg. cluster size : 5.43
    Right censoring rate : 0.34
    Covariates : lognormal(0, 1)
    Coefficients : 0.6931, 1.0986
    Frailty : pvf(0.3)
    Baseline hazard : (default) Lambda_0
     = function (t, c = 0.01, d = 4.6) (c * t)^d
    >
    > # An oscillating baseline hazard
    > dat.5 <- genfrail(lambda_0=function(t, tau=4.6, C=0.01, A=2, f=0.1)
    + A^sin(f*pi*t) * (tau*(C*t)^tau)/t)
    >
    > # Uniform censorship with 0.25 censoring rate
    > dat.6 <- genfrail(N = 300, K = 2,
    + beta = c(log(2),log(3)),
    + frailty = "gamma", theta = 2,
    + censor.distr = "uniform",
    + censor.param = c(50, 150),
    + censor.rate = 0.25,
    + Lambda_0_inv=function(t, tau=4.6, C=0.01) (t^(1/tau))/C)
    Error in integrate(function(t) efail(t) * censor.density(t, lower, upper), :
     roundoff error was detected
    Calls: genfrail -> uniroot -> f -> integrate
    Execution halted
Flavor: r-devel-windows-ix86+x86_64