[r-inla] Error in inla.inlaprogram.has.crashed
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Naien Tang
Nov 7, 2018, 5:37:31 PM11/7/18
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I ran the following model and the program is crashed.
Does anyone has any suggestion?
Many thanks!
> formula.st.ST2_2 <- income_2 ~ f(ID,model="besag",graph=county.adj,constr = TRUE, scale.model = TRUE) +f(year,model="rw2")
> model.st.ST2_2 <- inla(formula.st.ST2_2,family="gaussian",data=county_data_all,
+ control.predictor=list(compute=TRUE,link=link_st),
+ control.compute=list(dic=TRUE,cpo=TRUE),lincomb=lcs.st,verbose=TRUE )
hgid: b84cb08f11c9 date: Thu Jul 12 13:38:25 2018 +0300
Report bugs to <he...@r-inla.org>
Processing file [C:\Users\ntang\AppData\Local\Temp\RtmpYzwzqv\filedb06b9443f/Model.ini] max_threads=[4]
inla_build...
number of sections=[16]
parse section=[0] name=[INLA.libR] type=[LIBR]
inla_parse_libR...
section[INLA.libR]
R_HOME=[C:/PROGRA~1/R/R-35~1.0]
parse section=[8] name=[INLA.Expert] type=[EXPERT]
inla_parse_expert...
section[INLA.Expert]
disable.gaussian.check=[0]
cpo.manual=[0]
jp.file=[(null)]
jp.model=[(null)]
parse section=[1] name=[INLA.Model] type=[PROBLEM]
inla_parse_problem...
name=[INLA.Model]
openmp.strategy=[default]
pardiso-library installed and working? = [no]
smtp = [taucs]
strategy = [default]
store results in directory=[C:\Users\ntang\AppData\Local\Temp\RtmpYzwzqv\filedb06b9443f/results.files]
output:
cpo=[1]
po=[0]
dic=[1]
kld=[1]
mlik=[1]
q=[0]
graph=[0]
gdensity=[0]
hyperparameters=[1]
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[3] name=[Predictor] type=[PREDICTOR]
inla_parse_predictor ...
section=[Predictor]
dir=[predictor]
PRIOR->name=[loggamma]
hyperid=[53001|Predictor]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 1e-005]
initialise log_precision[12]
fixed=[1]
user.scale=[1]
n=[21749]
m=[0]
ndata=[21749]
compute=[1]
read offsets from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7]
read n=[43498] entries from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7]
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 0/21749 (idx,y) = (0, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 1/21749 (idx,y) = (1, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 2/21749 (idx,y) = (2, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 3/21749 (idx,y) = (3, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 4/21749 (idx,y) = (4, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 5/21749 (idx,y) = (5, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 6/21749 (idx,y) = (6, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 7/21749 (idx,y) = (7, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 8/21749 (idx,y) = (8, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb03511da7] 9/21749 (idx,y) = (9, 0)
read link.fitted.values from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1]
read n=[43498] entries from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1]
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 0/21749 (idx,y) = (0, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 1/21749 (idx,y) = (1, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 2/21749 (idx,y) = (2, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 3/21749 (idx,y) = (3, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 4/21749 (idx,y) = (4, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 5/21749 (idx,y) = (5, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 6/21749 (idx,y) = (6, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 7/21749 (idx,y) = (7, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 8/21749 (idx,y) = (8, 1.#QNAN)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0728d4bd1] 9/21749 (idx,y) = (9, 1.#QNAN)
Aext=[(null)]
AextPrecision=[1e+008]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[2] name=[INLA.Data1] type=[DATA]
inla_parse_data [section 1]...
tag=[INLA.Data1]
family=[GAUSSIAN]
likelihood=[GAUSSIAN]
file->name=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb047e53b02]
file->name=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb01f454d69]
read n=[55926] entries from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb047e53b02]
0/18642 (idx,a,y,d) = (0, 1, -0.194172, 1)
1/18642 (idx,a,y,d) = (1, 1, 0.36767, 1)
2/18642 (idx,a,y,d) = (2, 1, 0.407838, 1)
3/18642 (idx,a,y,d) = (3, 1, -0.883596, 1)
4/18642 (idx,a,y,d) = (4, 1, -0.260607, 1)
5/18642 (idx,a,y,d) = (5, 1, -0.208926, 1)
6/18642 (idx,a,y,d) = (6, 1, 0.078903, 1)
7/18642 (idx,a,y,d) = (7, 1, 1.39882, 1)
8/18642 (idx,a,y,d) = (8, 1, 0.54881, 1)
9/18642 (idx,a,y,d) = (9, 1, 0.0731038, 1)
likelihood.variant=[0]
initialise log_precision[4]
fixed=[0]
PRIOR->name=[loggamma]
hyperid=[65001|INLA.Data1]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 5e-005]
Link model [IDENTITY]
Link order [-1]
Link variant [-1]
Link ntheta [0]
mix.use[0]
parse section=[5] name=[ID] type=[FFIELD]
inla_parse_ffield...
section=[ID]
dir=[random.effect00000001]
model=[besag]
PRIOR->name=[loggamma]
hyperid=[8001|ID]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 5e-005]
correct=[-1]
constr=[0]
diagonal=[1.01511e-005]
id.names=<not present>
compute=[1]
nrep=[1]
ngroup=[1]
read covariates from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7]
read n=[43498] entries from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7]
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 0/21749 (idx,y) = (0, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 1/21749 (idx,y) = (1, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 2/21749 (idx,y) = (2, 2)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 3/21749 (idx,y) = (3, 3)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 4/21749 (idx,y) = (4, 4)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 5/21749 (idx,y) = (5, 5)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 6/21749 (idx,y) = (6, 6)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 7/21749 (idx,y) = (7, 7)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 8/21749 (idx,y) = (8, 8)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb04dab65d7] 9/21749 (idx,y) = (9, 9)
read graph from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0245e193c]
file for locations=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb02f7c448c]
nlocations=[3107]
locations[0]=[1]
locations[1]=[2]
locations[2]=[3]
locations[3]=[4]
locations[4]=[5]
locations[5]=[6]
locations[6]=[7]
locations[7]=[8]
locations[8]=[9]
locations[9]=[10]
initialise log_precision[4]
fixed=[0]
adjust.for.con.comp[1]
scale.model[1]
connected component[0] size[3105] scale[0.609826]
connected component[1] size[1] scale[-1]
connected component[2] size[1] scale[-1]
scale.model: prec_scale[0.609826]
read extra constraint from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb093e527]
Constraint[0]
A[0] = 1.000000
A[1] = 1.000000
A[2] = 1.000000
A[3] = 1.000000
A[4] = 1.000000
A[5] = 1.000000
A[6] = 1.000000
A[7] = 1.000000
A[8] = 1.000000
A[9] = 1.000000
A[10] = 1.000000
e[0] = 0.000000
rank-deficiency is *defined* [1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[6] name=[year] type=[FFIELD]
inla_parse_ffield...
section=[year]
dir=[random.effect00000002]
model=[rw2]
PRIOR->name=[loggamma]
hyperid=[5001|year]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 5e-005]
correct=[-1]
constr=[1]
diagonal=[1.01511e-005]
id.names=<not present>
compute=[1]
nrep=[1]
ngroup=[1]
read covariates from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76]
read n=[43498] entries from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76]
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 0/21749 (idx,y) = (0, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 1/21749 (idx,y) = (1, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 2/21749 (idx,y) = (2, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 3/21749 (idx,y) = (3, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 4/21749 (idx,y) = (4, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 5/21749 (idx,y) = (5, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 6/21749 (idx,y) = (6, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 7/21749 (idx,y) = (7, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 8/21749 (idx,y) = (8, 0)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07cc77d76] 9/21749 (idx,y) = (9, 0)
file for locations=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb07c124c6]
nlocations=[7]
locations[0]=[1]
locations[1]=[2]
locations[2]=[3]
locations[3]=[4]
locations[4]=[5]
locations[5]=[6]
locations[6]=[7]
cyclic=[0]
initialise log_precision[4]
fixed=[0]
scale.model[0]
computed/guessed rank-deficiency = [2]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[4] name=[(Intercept)] type=[LINEAR]
inla_parse_linear...
section[(Intercept)]
dir=[fixed.effect00000001]
file for covariates=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792]
read n=[43498] entries from file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792]
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 0/21749 (idx,y) = (0, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 1/21749 (idx,y) = (1, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 2/21749 (idx,y) = (2, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 3/21749 (idx,y) = (3, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 4/21749 (idx,y) = (4, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 5/21749 (idx,y) = (5, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 6/21749 (idx,y) = (6, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 7/21749 (idx,y) = (7, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 8/21749 (idx,y) = (8, 1)
file=[C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb0e484792] 9/21749 (idx,y) = (9, 1)
prior mean=[0]
prior precision=[0]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
Index table: number of entries[4], total length[24864]
tag start-index length
Predictor 0 21749
ID 21749 3107
year 24856 7
(Intercept) 24863 1
parse section=[7] name=[INLA.Parameters] type=[INLA]
inla_parse_INLA...
section[INLA.Parameters]
lincomb.derived.only = [Yes]
lincomb.derived.correlation.matrix = [No]
global_node.factor = 2.000
global_node.degree = 2147483647
reordering = -1
Contents of ai_param 00000000063C5F20
Optimiser: DEFAULT METHOD
Option for domin-BFGS: epsx = 0.005
Option for domin-BFGS: epsf = 1e-005 (rounding error)
Option for domin-BFGS: epsg = 0.005
Option for GSL-BFGS2: tol = 0.1
Option for GSL-BFGS2: step_size = 1
Option for GSL-BFGS2: epsx = 0.005
Option for GSL-BFGS2: epsf = 0.000353553
Option for GSL-BFGS2: epsg = 0.005
Restart: 0
Mode known: No
Gaussian approximation:
abserr_func = 0.0005
abserr_step = 0.0005
optpar_fp = 0
optpar_nr_step_factor = -0.1
Gaussian data: Yes
Strategy: Use a mean-skew corrected Gaussian by fitting a Skew-Normal
Fast mode: On
Use linear approximation to log(|Q +c|)? Yes
Method: Compute the derivative exact
Parameters for improved approximations
Number of points evaluate: 9
Step length to compute derivatives numerically: 0.000100002
Stencil to compute derivatives numerically: 5
Cutoff value to construct local neigborhood: 0.0001
Log calculations: On
Log calculated marginal for the hyperparameters: On
Integration strategy: Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
f0 (CCD only): 1.100000
dz (GRID only): 0.750000
Adjust weights (GRID only): On
Difference in log-density limit (GRID only): 6.000000
Skip configurations with (presumed) small density (GRID only): On
Gradient is computed using Central difference with step-length 0.010000
Hessian is computed using Central difference with step-length 0.100000
Hessian matrix is forced to be a diagonal matrix? [No]
Compute effective number of parameters? [Yes]
Perform a Monte Carlo error-test? [No]
Interpolator [Auto]
CPO required diff in log-density [3]
Stupid search mode:
Status [On]
Max iter [1000]
Factor [1.05]
Numerical integration of hyperparameters:
Maximum number of function evaluations [100000]
Relative error ....................... [1e-005]
Absolute error ....................... [1e-006]
To stabilise the numerical optimisation:
Minimum value of the -Hessian [-1.#INF]
CPO manual calculation[No]
Laplace-correction is Disabled.
section=[9] name=[lincomb.lc1] type=[LINCOMB]
inla_parse_lincomb...
secname = [lincomb.lc1]
filename [C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb040f363a9]
file.offset [0]
precision [1e+009]
Open file [C:/Users/ntang/AppData/Local/Temp/RtmpYzwzqv/filedb06b9443f/data.files/filedb040f363a9] at location [0]
Number of sections [2]
Section [0] is named [year]
Section has offset=[24856] and n=[7]
npairs=[1]
Section [1] is named [year1]
*** ERROR *** Section no [1] named [year1] in file [101702240] offset[ 0] is unknown.
Error in inla.inlaprogram.has.crashed() :
The inla-program exited with an error. Unless you interupted it yourself, please rerun with verbose=TRUE and check the output carefully.
If this does not help, please contact the developers at <he...@r-inla.org>.
Finn Lindgren
Nov 7, 2018, 5:53:11 PM11/7/18
to Naien Tang, R-inla discussion group
Hi,
The error appears when parsing the lincomb information.
Double check that what you’re supplying there is correct (the lcs.st variable).
Running str(lcs.st) may help
Finn
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