Error in re-building vignettes:
  ...
Loading required package: sp
Loading required package: xtable
Loading required package: polyCub
This is surveillance 1.15.0. For overview type ‘help(surveillance)’.
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting glm.nb model with alpha=0.225966923076071
glrnb: Fitting glm.nb model with alpha=0.225966923076071
glrnb: Fitting glm.nb model with alpha=0.225966923076071
glrnb: Fitting glm.nb model with alpha=0.225966923076071
glrnb: Fitting glm.nb model with alpha=0.225966923076071
glrnb: Fitting glm.nb model with alpha=0.225966923076071
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
glrnb: Fitting Poisson model because alpha == 0
Doing computations: FALSE
Loading required package: splines
Loading required package: gamlss.data
Loading required package: gamlss.dist
Loading required package: MASS
Loading required package: nlme
Loading required package: parallel
 **********   GAMLSS Version 5.0-6  ********** 
For more on GAMLSS look at http://www.gamlss.org/
Type gamlssNews() to see new features/changes/bug fixes.

Doing computations: FALSE
Doing computations: FALSE
Loading required namespace: spdep
Note: range of maximum neighbour order by region is 3-5
Warning in scores.oneStepAhead(oneStepAhead(measlesFit_powerlaw, tp = 1,  :
  Time points are reversed in the result (historical default).
  Note that this will change with the next version of "surveillance".
  Set the 'reverse' argument explicitly to avoid this warning.
Warning in scores.oneStepAhead(X[[i]], ...) :
  Time points are reversed in the result (historical default).
  Note that this will change with the next version of "surveillance".
  Set the 'reverse' argument explicitly to avoid this warning.
Warning in scores.oneStepAhead(X[[i]], ...) :
  Time points are reversed in the result (historical default).
  Note that this will change with the next version of "surveillance".
  Set the 'reverse' argument explicitly to avoid this warning.
Warning in scores.oneStepAhead(X[[i]], ...) :
  Time points are reversed in the result (historical default).
  Note that this will change with the next version of "surveillance".
  Set the 'reverse' argument explicitly to avoid this warning.
Warning in scores.oneStepAhead(X[[i]], ...) :
  Time points are reversed in the result (historical default).
  Note that this will change with the next version of "surveillance".
  Set the 'reverse' argument explicitly to avoid this warning.
Warning in scores.oneStepAhead(X[[i]], ...) :
  Time points are reversed in the result (historical default).
  Note that this will change with the next version of "surveillance".
  Set the 'reverse' argument explicitly to avoid this warning.
Warning in scores.oneStepAhead(X[[i]], ...) :
  Time points are reversed in the result (historical default).
  Note that this will change with the next version of "surveillance".
  Set the 'reverse' argument explicitly to avoid this warning.
Doing computations: FALSE
Warning in `[.epidata`(x, seq_len(n), , drop = FALSE) :
  dropped class "epidata": subsetting blocks not allowed
Initialized 1 log-baseline interval:  0.00 92.55
Initial parameter vector:  1 1 1 1 0
Computing OSAIC weights for 4 epidemic covariates based on 1000 simulations ...
Initialized 1 log-baseline interval:  0.00 92.55
Initial parameter vector:  1 1 1 1 1 1 0
Computing OSAIC weights for 4 epidemic covariates based on 1000 simulations ...
Doing computations: FALSE
Note: auto-generated neighbourhood matrix contains 1 island
no epidemic component in model
Setting up the model environment ...
'imdfit_powerlaw' was fit with disabled 'cumCIF' -> calculate it now ...
Note: added the 'tau' component to object 'imdfit_powerlaw' for future use.
Quitting from lines 1080-1082 (twinstim.Rnw) 
Error: processing vignette ‘twinstim.Rnw’ failed with diagnostics:
identicalCRS(x, y) is not TRUE
Execution halted