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

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: get_restricted_ou
> ### Title: Convenience function for constructing restricted/reparameterised
> ###   OU parameterisation function.
> ### Aliases: get_restricted_ou
> 
> ### ** Examples
> 
> ### --- STEP 1: Make an example tree
> set.seed(0x5EEDL, kind='Super-Duper')
> ntips = 200
> k     = 2                 # No. of trait dimensions
> tr    = ape::rtree(ntips) 
> x0    = rnorm(k)
> 
> ### --- STEP 2: Make a model which has unrestricted H, fixed theta and diagonal Sigma_x'.
> repar = get_restricted_ou(H=NULL, theta=c(3,1), Sig='diag', lossmiss=NULL)
> mod   = glinv(tr, x0, X=NULL,
+               pardims =repar$nparams(k),
+               parfns  =repar$par,
+               parjacs =repar$jac,
+               parhess =repar$hess)
> # Actually, to save typing, the following short-cut call is the same as the above:
> # mod = glinv(tr, x0, X=NULL, repar=repar)
> 
> ### --- STEP 3: Set up parameters; H, theta, and sig_x needs to be concatenated
> H     = matrix(c(1,0,0,-1), k)
> theta = c(3,1)
> sig   = matrix(c(0.25,0,0,0.25), k)
> sig_x = t(chol(sig))
> par_truth = c(H=H, sig_x=c(0.5,0.5))
> 
> ### --- STEP 4: Get a simulated data set to toy with
> X = rglinv(mod, par=par_truth)
> set_tips(mod, X)
> 
> ### --- STEP 5: Make an unrestricted model object to compare with the one
> ### whose parameters are restricted.
> mod_unrestricted = glinv(tr, x0, X,
+                          pardims=nparams_ou(k),
+                          parfns=oupar,
+                          parjacs=oujac,
+                          parhess=ouhess)
Error in glinv(tr, x0, X, pardims = nparams_ou(k), parfns = oupar, parjacs = oujac,  : 
  All dimensions at Node #1 are either lost or missing
Execution halted
Running examples in ‘glinvci-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: get_restricted_ou
> ### Title: Convenience function for constructing restricted/reparameterised
> ###   OU parameterisation function.
> ### Aliases: get_restricted_ou
> 
> ### ** Examples
> 
> ### --- STEP 1: Make an example tree
> set.seed(0x5EEDL, kind='Super-Duper')
> ntips = 200
> k     = 2                 # No. of trait dimensions
> tr    = ape::rtree(ntips) 
> x0    = rnorm(k)
> 
> ### --- STEP 2: Make a model which has unrestricted H, fixed theta and diagonal Sigma_x'.
> repar = get_restricted_ou(H=NULL, theta=c(3,1), Sig='diag', lossmiss=NULL)
> mod   = glinv(tr, x0, X=NULL,
+               pardims =repar$nparams(k),
+               parfns  =repar$par,
+               parjacs =repar$jac,
+               parhess =repar$hess)
> # Actually, to save typing, the following short-cut call is the same as the above:
> # mod = glinv(tr, x0, X=NULL, repar=repar)
> 
> ### --- STEP 3: Set up parameters; H, theta, and sig_x needs to be concatenated
> H     = matrix(c(1,0,0,-1), k)
> theta = c(3,1)
> sig   = matrix(c(0.25,0,0,0.25), k)
> sig_x = t(chol(sig))
> par_truth = c(H=H, sig_x=c(0.5,0.5))
> 
> ### --- STEP 4: Get a simulated data set to toy with
> X = rglinv(mod, par=par_truth)
> set_tips(mod, X)
> 
> ### --- STEP 5: Make an unrestricted model object to compare with the one
> ### whose parameters are restricted.
> mod_unrestricted = glinv(tr, x0, X,
+                          pardims=nparams_ou(k),
+                          parfns=oupar,
+                          parjacs=oujac,
+                          parhess=ouhess)
Error in glinv(tr, x0, X, pardims = nparams_ou(k), parfns = oupar, parjacs = oujac,  : 
  All dimensions at Node #1 are either lost or missing
Execution halted
Running examples in ‘glinvci-Ex.R’ failed
The error most likely occurred in:

> ### Name: get_restricted_ou
> ### Title: Convenience function for constructing restricted/reparameterised
> ###   OU parameterisation function.
> ### Aliases: get_restricted_ou
> 
> ### ** Examples
> 
> ### --- STEP 1: Make an example tree
> set.seed(0x5EEDL, kind='Super-Duper')
> ntips = 200
> k     = 2                 # No. of trait dimensions
> tr    = ape::rtree(ntips) 
> x0    = rnorm(k)
> 
> ### --- STEP 2: Make a model which has unrestricted H, fixed theta and diagonal Sigma_x'.
> repar = get_restricted_ou(H=NULL, theta=c(3,1), Sig='diag', lossmiss=NULL)
> mod   = glinv(tr, x0, X=NULL,
+               pardims =repar$nparams(k),
+               parfns  =repar$par,
+               parjacs =repar$jac,
+               parhess =repar$hess)
> # Actually, to save typing, the following short-cut call is the same as the above:
> # mod = glinv(tr, x0, X=NULL, repar=repar)
> 
> ### --- STEP 3: Set up parameters; H, theta, and sig_x needs to be concatenated
> H     = matrix(c(1,0,0,-1), k)
> theta = c(3,1)
> sig   = matrix(c(0.25,0,0,0.25), k)
> sig_x = t(chol(sig))
> par_truth = c(H=H, sig_x=c(0.5,0.5))
> 
> ### --- STEP 4: Get a simulated data set to toy with
> X = rglinv(mod, par=par_truth)
> set_tips(mod, X)
> 
> ### --- STEP 5: Make an unrestricted model object to compare with the one
> ### whose parameters are restricted.
> mod_unrestricted = glinv(tr, x0, X,
+                          pardims=nparams_ou(k),
+                          parfns=oupar,
+                          parjacs=oujac,
+                          parhess=ouhess)
Error in glinv(tr, x0, X, pardims = nparams_ou(k), parfns = oupar, parjacs = oujac,  : 
  All dimensions at Node #1 are either lost or missing
Execution halted
Running examples in ‘glinvci-Ex.R’ failed
The error most likely occurred in:

> ### Name: get_restricted_ou
> ### Title: Convenience function for constructing restricted/reparameterised
> ###   OU parameterisation function.
> ### Aliases: get_restricted_ou
> 
> ### ** Examples
> 
> ### --- STEP 1: Make an example tree
> set.seed(0x5EEDL, kind='Super-Duper')
> ntips = 200
> k     = 2                 # No. of trait dimensions
> tr    = ape::rtree(ntips) 
> x0    = rnorm(k)
> 
> ### --- STEP 2: Make a model which has unrestricted H, fixed theta and diagonal Sigma_x'.
> repar = get_restricted_ou(H=NULL, theta=c(3,1), Sig='diag', lossmiss=NULL)
> mod   = glinv(tr, x0, X=NULL,
+               pardims =repar$nparams(k),
+               parfns  =repar$par,
+               parjacs =repar$jac,
+               parhess =repar$hess)
> # Actually, to save typing, the following short-cut call is the same as the above:
> # mod = glinv(tr, x0, X=NULL, repar=repar)
> 
> ### --- STEP 3: Set up parameters; H, theta, and sig_x needs to be concatenated
> H     = matrix(c(1,0,0,-1), k)
> theta = c(3,1)
> sig   = matrix(c(0.25,0,0,0.25), k)
> sig_x = t(chol(sig))
> par_truth = c(H=H, sig_x=c(0.5,0.5))
> 
> ### --- STEP 4: Get a simulated data set to toy with
> X = rglinv(mod, par=par_truth)
> set_tips(mod, X)
> 
> ### --- STEP 5: Make an unrestricted model object to compare with the one
> ### whose parameters are restricted.
> mod_unrestricted = glinv(tr, x0, X,
+                          pardims=nparams_ou(k),
+                          parfns=oupar,
+                          parjacs=oujac,
+                          parhess=ouhess)
Error in glinv(tr, x0, X, pardims = nparams_ou(k), parfns = oupar, parjacs = oujac,  : 
  All dimensions at Node #1 are either lost or missing
Execution halted
Running examples in 'glinvci-Ex.R' failed
The error most likely occurred in:

> ### Name: get_restricted_ou
> ### Title: Convenience function for constructing restricted/reparameterised
> ###   OU parameterisation function.
> ### Aliases: get_restricted_ou
> 
> ### ** Examples
> 
> ### --- STEP 1: Make an example tree
> set.seed(0x5EEDL, kind='Super-Duper')
> ntips = 200
> k     = 2                 # No. of trait dimensions
> tr    = ape::rtree(ntips) 
> x0    = rnorm(k)
> 
> ### --- STEP 2: Make a model which has unrestricted H, fixed theta and diagonal Sigma_x'.
> repar = get_restricted_ou(H=NULL, theta=c(3,1), Sig='diag', lossmiss=NULL)
> mod   = glinv(tr, x0, X=NULL,
+               pardims =repar$nparams(k),
+               parfns  =repar$par,
+               parjacs =repar$jac,
+               parhess =repar$hess)
> # Actually, to save typing, the following short-cut call is the same as the above:
> # mod = glinv(tr, x0, X=NULL, repar=repar)
> 
> ### --- STEP 3: Set up parameters; H, theta, and sig_x needs to be concatenated
> H     = matrix(c(1,0,0,-1), k)
> theta = c(3,1)
> sig   = matrix(c(0.25,0,0,0.25), k)
> sig_x = t(chol(sig))
> par_truth = c(H=H, sig_x=c(0.5,0.5))
> 
> ### --- STEP 4: Get a simulated data set to toy with
> X = rglinv(mod, par=par_truth)
> set_tips(mod, X)
> 
> ### --- STEP 5: Make an unrestricted model object to compare with the one
> ### whose parameters are restricted.
> mod_unrestricted = glinv(tr, x0, X,
+                          pardims=nparams_ou(k),
+                          parfns=oupar,
+                          parjacs=oujac,
+                          parhess=ouhess)
Error in glinv(tr, x0, X, pardims = nparams_ou(k), parfns = oupar, parjacs = oujac,  : 
  All dimensions at Node #1 are either lost or missing
Execution halted