glmmrBase

for GNU extensions in Makefiles

GNU make is a SystemRequirements.

installed package size

installed size is 170.2Mb
  sub-directories of 1Mb or more:
    libs  168.9Mb

examples

Running examples in ‘glmmrBase-Ex.R’ failed
The error most likely occurred in:

> ### Name: Model
> ### Title: A GLMM Model
> ### Aliases: Model
> 
> ### ** Examples
> 
> 
> ## ------------------------------------------------
> ## Method `Model$new`
> ## ------------------------------------------------
> 
> ## Don't show: 
> setParallel(FALSE) 
> ## End(Don't show)
> # For more examples, see the examples for MCML.
> 
> #create a data frame describing a cross-sectional parallel cluster
> #randomised trial
> df <- nelder(~(cl(10)*t(5)) > ind(10))
> df$int <- 0
> df[df$cl > 5, 'int'] <- 1
> mod <- Model$new(
+   formula = ~ factor(t) + int - 1 + (1|gr(cl)) + (1|gr(cl,t)),
+   data = df,
+   family = stats::gaussian()
+ )
> 
> # We can also include the outcome data in the model initialisation. 
> # For example, simulating data and creating a new object:
> df$y <- mod$sim_data()
> 
> mod <- Model$new(
+   formula = y ~ factor(t) + int - 1 + (1|gr(cl)) + (1|gr(cl,t)),
+   data = df,
+   fami
...[truncated]...
numeric(Orange$Tree)
> ##D 
> ##D # Here we can specify the model as a function. 
> ##D 
> ##D model <- Model$new(
> ##D   circumference ~ Asym/(1 + exp((xmid - (age))/scal)) - 1 + (Asym|gr(Tree)),
> ##D   data = Orange,
> ##D   family = gaussian(),
> ##D   mean = c(200,725,350),
> ##D   covariance = c(500),
> ##D   var_par = 50
> ##D )
> ##D 
> ##D # for this example, we will use MCEM with adaptive MCMC sample sizes
> ##D 
> ##D nfit <- model$MCML(method = "mcem.adapt", iter.sampling = 1000)
> ##D 
> ##D summary(nfit)
> ##D summary(nm1)
> ##D 
> ##D 
> ## End(Not run)
> 
> ## ------------------------------------------------
> ## Method `Model$fit`
> ## ------------------------------------------------
> 
> # Simulated trial data example using REML
> data(SimTrial,package = "glmmrBase")
> fit1 <- Model$new(
+   formula = y ~ int + factor(t) - 1 + (1|grlog(cl)*ar0log(t)),
+   data = SimTrial,
+   family = gaussian()
+ )$fit(reml = TRUE)
Error: Exponent fail: nan^1.000000
Execution halted

for GNU extensions in Makefiles

GNU make is a SystemRequirements.

installed package size

installed size is 179.8Mb
  sub-directories of 1Mb or more:
    libs  178.6Mb

for GNU extensions in Makefiles

GNU make is a SystemRequirements.

installed package size

installed size is  5.7Mb
  sub-directories of 1Mb or more:
    libs   4.5Mb

examples

Running examples in ‘glmmrBase-Ex.R’ failed
The error most likely occurred in:

> ### Name: Model
> ### Title: A GLMM Model
> ### Aliases: Model
> 
> ### ** Examples
> 
> 
> ## ------------------------------------------------
> ## Method `Model$new`
> ## ------------------------------------------------
> 
> ## Don't show: 
> setParallel(FALSE) 
> ## End(Don't show)
> # For more examples, see the examples for MCML.
> 
> #create a data frame describing a cross-sectional parallel cluster
> #randomised trial
> df <- nelder(~(cl(10)*t(5)) > ind(10))
> df$int <- 0
> df[df$cl > 5, 'int'] <- 1
> mod <- Model$new(
+   formula = ~ factor(t) + int - 1 + (1|gr(cl)) + (1|gr(cl,t)),
+   data = df,
+   family = stats::gaussian()
+ )
> 
> # We can also include the outcome data in the model initialisation. 
> # For example, simulating data and creating a new object:
> df$y <- mod$sim_data()
> 
> mod <- Model$new(
+   formula = y ~ factor(t) + int - 1 + (1|gr(cl)) + (1|gr(cl,t)),
+   data = df,
+   fami
...[truncated]...
numeric(Orange$Tree)
> ##D 
> ##D # Here we can specify the model as a function. 
> ##D 
> ##D model <- Model$new(
> ##D   circumference ~ Asym/(1 + exp((xmid - (age))/scal)) - 1 + (Asym|gr(Tree)),
> ##D   data = Orange,
> ##D   family = gaussian(),
> ##D   mean = c(200,725,350),
> ##D   covariance = c(500),
> ##D   var_par = 50
> ##D )
> ##D 
> ##D # for this example, we will use MCEM with adaptive MCMC sample sizes
> ##D 
> ##D nfit <- model$MCML(method = "mcem.adapt", iter.sampling = 1000)
> ##D 
> ##D summary(nfit)
> ##D summary(nm1)
> ##D 
> ##D 
> ## End(Not run)
> 
> ## ------------------------------------------------
> ## Method `Model$fit`
> ## ------------------------------------------------
> 
> # Simulated trial data example using REML
> data(SimTrial,package = "glmmrBase")
> fit1 <- Model$new(
+   formula = y ~ int + factor(t) - 1 + (1|grlog(cl)*ar0log(t)),
+   data = SimTrial,
+   family = gaussian()
+ )$fit(reml = TRUE)
Error: Exponent fail: nan^1.000000
Execution halted