Skip to content

Instantly share code, notes, and snippets.

@mja
Created May 6, 2014 09:32
Show Gist options
  • Save mja/ece0addcc30bf493c7d2 to your computer and use it in GitHub Desktop.
Save mja/ece0addcc30bf493c7d2 to your computer and use it in GitHub Desktop.
Running the bym2 model in INLA
> n <- nrow(CC)
> Q <- INLA:::inla.pc.bym.Q(border, scale.model=TRUE)
> u <- .2/.31
> alpha <- .01
> phi.u <- .5
> phi.alpha <- 2/3
> formula2 <- agr ~ age + sex + age:sex +
+ f(geo, model='bym2', graph=border,
+ constr=TRUE, scale.model=TRUE,
+ hyper=list(phi=list(prior='pc',
+ param=c(phi.u, phi.alpha),
+ initial=-3),
+ prec=list(prior='pc.prec',
+ param=c(u, alpha),
+ initial=5)))
> agr_geo <- inla(formula2, family='gaussian', data=CC, verbose=TRUE)
hgid: f4b2fa41b99b date: Thu Apr 03 15:35:52 2014 +0200
Report bugs to <[email protected]>
Processing file [/tmp/RtmpwnHhDH/file21967666466b/Model.ini] max_threads=[12]
inla_build...
number of sections=[11]
parse section=[0] name=[INLA.Model] type=[PROBLEM]
inla_parse_problem...
name=[INLA.Model]
openmp.strategy=[default]
store results in directory=[/tmp/RtmpwnHhDH/file21967666466b/results.files]
output:
cpo=[0]
po=[0]
dic=[0]
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=[2] name=[Predictor] type=[PREDICTOR]
inla_parse_predictor ...
section=[Predictor]
dir=[predictor]
PRIOR->name=[loggamma]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 1e-05]
initialise log_precision[11]
fixed=[1]
user.scale=[1]
n=[14270]
m=[0]
ndata=[14270]
compute=[0]
read offsets from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 0/14270 (idx,y) = (0, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 1/14270 (idx,y) = (1, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 2/14270 (idx,y) = (2, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 3/14270 (idx,y) = (3, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 4/14270 (idx,y) = (4, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 5/14270 (idx,y) = (5, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 6/14270 (idx,y) = (6, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 7/14270 (idx,y) = (7, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 8/14270 (idx,y) = (8, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 9/14270 (idx,y) = (9, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 10/14270 (idx,y) = (10, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 11/14270 (idx,y) = (11, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 12/14270 (idx,y) = (12, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 13/14270 (idx,y) = (13, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 14/14270 (idx,y) = (14, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 15/14270 (idx,y) = (15, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 16/14270 (idx,y) = (16, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 17/14270 (idx,y) = (17, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 18/14270 (idx,y) = (18, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e5bbe79] 19/14270 (idx,y) = (19, 0)
Aext=[(null)]
AextPrecision=[1e+08]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[1] name=[INLA.Data1] type=[DATA]
inla_parse_data [section 1]...
tag=[INLA.Data1]
family=[GAUSSIAN]
likelihood=[GAUSSIAN]
file->name=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e46977d]
file->name=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219675645f27]
read n=[42810] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21961e46977d]
0/14270 (idx,a,y,d) = (0, 1, 3.88889, 1)
1/14270 (idx,a,y,d) = (1, 1, 4.5, 1)
2/14270 (idx,a,y,d) = (2, 1, 3.125, 1)
3/14270 (idx,a,y,d) = (3, 1, 3.88889, 1)
4/14270 (idx,a,y,d) = (4, 1, 4.25, 1)
5/14270 (idx,a,y,d) = (5, 1, 3.625, 1)
6/14270 (idx,a,y,d) = (6, 1, 4, 1)
7/14270 (idx,a,y,d) = (7, 1, 3.5, 1)
8/14270 (idx,a,y,d) = (8, 1, 3.25, 1)
9/14270 (idx,a,y,d) = (9, 1, 3.875, 1)
10/14270 (idx,a,y,d) = (10, 1, 3.375, 1)
11/14270 (idx,a,y,d) = (11, 1, 3.22222, 1)
12/14270 (idx,a,y,d) = (12, 1, 2.875, 1)
13/14270 (idx,a,y,d) = (13, 1, 4.22222, 1)
14/14270 (idx,a,y,d) = (14, 1, 3.875, 1)
15/14270 (idx,a,y,d) = (15, 1, 3, 1)
16/14270 (idx,a,y,d) = (16, 1, 2.875, 1)
17/14270 (idx,a,y,d) = (17, 1, 3.625, 1)
18/14270 (idx,a,y,d) = (18, 1, 2.625, 1)
19/14270 (idx,a,y,d) = (19, 1, 2.375, 1)
use variant [0]
bit 0 is off
bit 1 is off
bit 2 is off
bit 3 is off
initialise log_precision[4]
fixed=[0]
PRIOR->name=[loggamma]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 5e-05]
Link model [IDENTITY]
Link order [-1]
Link ntheta [0]
mix.use[0]
parse section=[9] name=[geo] type=[FFIELD]
inla_parse_ffield...
section=[geo]
dir=[random.effect00000001]
model=[bym2]
PRIOR0->name=[pcprec]
PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR0->PARAMETERS0=[0.645161 0.01]
PRIOR1->name=[table]
PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)/(1 + exp(x))]
PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x/(1 - x))]
PRIOR1->table=[table: /tmp/RtmpwnHhDH/file21967666466b/data.files/file2196381dfd82]
constr=[0]
diagonal=[9.99978e-07]
id.names=<not present>
compute=[1]
nrep=[1]
ngroup=[1]
read covariates from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 0/14270 (idx,y) = (0, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 1/14270 (idx,y) = (1, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 2/14270 (idx,y) = (2, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 3/14270 (idx,y) = (3, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 4/14270 (idx,y) = (4, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 5/14270 (idx,y) = (5, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 6/14270 (idx,y) = (6, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 7/14270 (idx,y) = (7, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 8/14270 (idx,y) = (8, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 9/14270 (idx,y) = (9, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 10/14270 (idx,y) = (10, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 11/14270 (idx,y) = (11, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 12/14270 (idx,y) = (12, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 13/14270 (idx,y) = (13, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 14/14270 (idx,y) = (14, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 15/14270 (idx,y) = (15, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 16/14270 (idx,y) = (16, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 17/14270 (idx,y) = (17, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 18/14270 (idx,y) = (18, 12)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219629a73474] 19/14270 (idx,y) = (19, 12)
read graph from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962d2afec7]
file for locations=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219650d89607]
nlocations=[249]
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]
locations[10]=[11]
locations[11]=[12]
locations[12]=[13]
locations[13]=[14]
locations[14]=[15]
locations[15]=[16]
locations[16]=[17]
locations[17]=[18]
locations[18]=[19]
locations[19]=[20]
initialise log_precision [5]
fixed=[0]
initialise phi_intern [-3]
fixed=[0]
adjust.for.con.comp[1]
scale.model[1]
scale.model: prec_scale[0.71926]
read extra constraint from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196833f0b7]
Constraint[0]
A[249] = 1.000000
A[250] = 1.000000
A[251] = 1.000000
A[252] = 1.000000
A[253] = 1.000000
A[254] = 1.000000
A[255] = 1.000000
A[256] = 1.000000
A[257] = 1.000000
A[258] = 1.000000
A[259] = 1.000000
A[260] = 1.000000
A[261] = 1.000000
A[262] = 1.000000
A[263] = 1.000000
A[264] = 1.000000
A[265] = 1.000000
A[266] = 1.000000
A[267] = 1.000000
A[268] = 1.000000
A[269] = 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] [ ]
section=[3] name=[(Intercept)] type=[LINEAR]
inla_parse_linear...
section[(Intercept)]
dir=[fixed.effect00000001]
file for covariates=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 0/14270 (idx,y) = (0, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 1/14270 (idx,y) = (1, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 2/14270 (idx,y) = (2, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 3/14270 (idx,y) = (3, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 4/14270 (idx,y) = (4, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 5/14270 (idx,y) = (5, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 6/14270 (idx,y) = (6, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 7/14270 (idx,y) = (7, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 8/14270 (idx,y) = (8, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 9/14270 (idx,y) = (9, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 10/14270 (idx,y) = (10, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 11/14270 (idx,y) = (11, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 12/14270 (idx,y) = (12, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 13/14270 (idx,y) = (13, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 14/14270 (idx,y) = (14, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 15/14270 (idx,y) = (15, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 16/14270 (idx,y) = (16, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 17/14270 (idx,y) = (17, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 18/14270 (idx,y) = (18, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219689edc8d] 19/14270 (idx,y) = (19, 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] [ ]
section=[4] name=[age] type=[LINEAR]
inla_parse_linear...
section[age]
dir=[fixed.effect00000002]
file for covariates=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 0/14270 (idx,y) = (0, 19)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 1/14270 (idx,y) = (1, 26)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 2/14270 (idx,y) = (2, 25)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 3/14270 (idx,y) = (3, 22)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 4/14270 (idx,y) = (4, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 5/14270 (idx,y) = (5, 27)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 6/14270 (idx,y) = (6, 43)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 7/14270 (idx,y) = (7, 28)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 8/14270 (idx,y) = (8, 22)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 9/14270 (idx,y) = (9, 24)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 10/14270 (idx,y) = (10, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 11/14270 (idx,y) = (11, 23)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 12/14270 (idx,y) = (12, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 13/14270 (idx,y) = (13, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 14/14270 (idx,y) = (14, 19)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 15/14270 (idx,y) = (15, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 16/14270 (idx,y) = (16, 42)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 17/14270 (idx,y) = (17, 29)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 18/14270 (idx,y) = (18, 28)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196684e3c6e] 19/14270 (idx,y) = (19, 22)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[5] name=[sexfemale] type=[LINEAR]
inla_parse_linear...
section[sexfemale]
dir=[fixed.effect00000003]
file for covariates=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 0/14270 (idx,y) = (0, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 1/14270 (idx,y) = (1, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 2/14270 (idx,y) = (2, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 3/14270 (idx,y) = (3, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 4/14270 (idx,y) = (4, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 5/14270 (idx,y) = (5, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 6/14270 (idx,y) = (6, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 7/14270 (idx,y) = (7, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 8/14270 (idx,y) = (8, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 9/14270 (idx,y) = (9, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 10/14270 (idx,y) = (10, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 11/14270 (idx,y) = (11, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 12/14270 (idx,y) = (12, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 13/14270 (idx,y) = (13, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 14/14270 (idx,y) = (14, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 15/14270 (idx,y) = (15, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 16/14270 (idx,y) = (16, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 17/14270 (idx,y) = (17, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 18/14270 (idx,y) = (18, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file219673b12b85] 19/14270 (idx,y) = (19, 1)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[6] name=[sexmale] type=[LINEAR]
inla_parse_linear...
section[sexmale]
dir=[fixed.effect00000004]
file for covariates=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 0/14270 (idx,y) = (0, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 1/14270 (idx,y) = (1, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 2/14270 (idx,y) = (2, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 3/14270 (idx,y) = (3, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 4/14270 (idx,y) = (4, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 5/14270 (idx,y) = (5, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 6/14270 (idx,y) = (6, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 7/14270 (idx,y) = (7, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 8/14270 (idx,y) = (8, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 9/14270 (idx,y) = (9, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 10/14270 (idx,y) = (10, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 11/14270 (idx,y) = (11, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 12/14270 (idx,y) = (12, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 13/14270 (idx,y) = (13, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 14/14270 (idx,y) = (14, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 15/14270 (idx,y) = (15, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 16/14270 (idx,y) = (16, 1)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 17/14270 (idx,y) = (17, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 18/14270 (idx,y) = (18, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21965f12e2dd] 19/14270 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[7] name=[age:sexfemale] type=[LINEAR]
inla_parse_linear...
section[age:sexfemale]
dir=[fixed.effect00000005]
file for covariates=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 0/14270 (idx,y) = (0, 19)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 1/14270 (idx,y) = (1, 26)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 2/14270 (idx,y) = (2, 25)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 3/14270 (idx,y) = (3, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 4/14270 (idx,y) = (4, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 5/14270 (idx,y) = (5, 27)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 6/14270 (idx,y) = (6, 43)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 7/14270 (idx,y) = (7, 28)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 8/14270 (idx,y) = (8, 22)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 9/14270 (idx,y) = (9, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 10/14270 (idx,y) = (10, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 11/14270 (idx,y) = (11, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 12/14270 (idx,y) = (12, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 13/14270 (idx,y) = (13, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 14/14270 (idx,y) = (14, 19)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 15/14270 (idx,y) = (15, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 16/14270 (idx,y) = (16, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 17/14270 (idx,y) = (17, 29)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 18/14270 (idx,y) = (18, 28)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file2196116b150d] 19/14270 (idx,y) = (19, 22)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[8] name=[age:sexmale] type=[LINEAR]
inla_parse_linear...
section[age:sexmale]
dir=[fixed.effect00000006]
file for covariates=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23]
read n=[28540] entries from file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23]
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 0/14270 (idx,y) = (0, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 1/14270 (idx,y) = (1, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 2/14270 (idx,y) = (2, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 3/14270 (idx,y) = (3, 22)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 4/14270 (idx,y) = (4, 21)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 5/14270 (idx,y) = (5, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 6/14270 (idx,y) = (6, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 7/14270 (idx,y) = (7, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 8/14270 (idx,y) = (8, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 9/14270 (idx,y) = (9, 24)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 10/14270 (idx,y) = (10, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 11/14270 (idx,y) = (11, 23)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 12/14270 (idx,y) = (12, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 13/14270 (idx,y) = (13, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 14/14270 (idx,y) = (14, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 15/14270 (idx,y) = (15, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 16/14270 (idx,y) = (16, 42)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 17/14270 (idx,y) = (17, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 18/14270 (idx,y) = (18, 0)
file=[/tmp/RtmpwnHhDH/file21967666466b/data.files/file21962fdcc23] 19/14270 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
Index table: number of entries[8], total length[14774]
tag start-index length
Predictor 0 14270
geo 14270 498
(Intercept) 14768 1
age 14769 1
sexfemale 14770 1
sexmale 14771 1
age:sexfemale 14772 1
age:sexmale 14773 1
parse section=[10] 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 0x2b1a480
Optimiser: DEFAULT METHOD
Option for domin-BFGS: epsx = 0.005
Option for domin-BFGS: epsf = 1e-05 (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 the Gaussian approximation
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: 3.36941e-05
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: Use points from Central Composite Design (CCD)
f0 (CCD only): 1.100000
dz (GRID only): 1.000000
Adjust weights (GRID only): On
Difference in log-density limit (GRID only): 2.500000
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-05]
Absolute error ....................... [1e-06]
To stabalise the numerical optimisation:
Minimum value of the -Hesssian [0]
CPO manual calculation[No]
inla_build: check for unused entries in[/tmp/RtmpwnHhDH/file21967666466b/Model.ini]
inla_INLA...
Strategy = [DEFAULT]
Size is [14774] and strategy [LARGE] is chosen
Size of graph=[14774] constraints=[1]
Found optimal reordering=[amdc] nnz(L)=[89990] and use_global_nodes(user)=[no]
List of hyperparameters:
theta[0] = [Log precision for the Gaussian observations]
theta[1] = [Log precision for geo]
theta[2] = [Logit phi for geo]
Optimise using DEFAULT METHOD
Max.post.marg(theta): log(dens) = -134498.510159 fn = 1 theta = 4.010000 5.000000 -3.000000
Max.post.marg(theta): log(dens) = -133082.794441 fn = 2 theta = 4.000000 5.000000 -2.990000
Max.post.marg(theta): log(dens) = -133081.483067 fn = 3 theta = 4.000000 4.990000 -3.000000
Max.post.marg(theta): log(dens) = -131682.215581 fn = 5 theta = 3.990000 5.000000 -3.000000
Max.post.marg(theta): log(dens) = -46591.414039 fn = 7 theta = 3.000001 4.998908 -2.999911
Max.post.marg(theta): log(dens) = -46590.132335 fn = 9 theta = 3.000001 4.988908 -2.999911
Max.post.marg(theta): log(dens) = -46119.632601 fn = 13 theta = 2.990001 4.998908 -2.999911
Max.post.marg(theta): log(dens) = -23767.692837 fn = 15 theta = -1.404464 4.994099 -2.999517
Max.post.marg(theta): log(dens) = -23703.310817 fn = 16 theta = -1.394464 4.994099 -2.999517
Iter=1 |grad|=6.43e+03 |x-x.old|=3.12 |f-f.old|=1.09e+05
Max.post.marg(theta): log(dens) = -23393.482796 fn = 22 theta = -1.344646 4.184838 -3.583914
Max.post.marg(theta): log(dens) = -23329.742066 fn = 23 theta = -1.334646 4.184838 -3.583914
Max.post.marg(theta): log(dens) = -20717.796653 fn = 29 theta = -0.806279 -3.098508 -8.843479
Max.post.marg(theta): log(dens) = -20659.653740 fn = 30 theta = -0.796279 -3.098508 -8.843479
file: smtp-taucs.c hgid: f4b2fa41b99b date: Thu Apr 03 15:35:52 2014 +0200
Function: GMRFLib_factorise_sparse_matrix_TAUCS(), Line: 829, Thread: 0
Fail to factorize Q. I will try to fix it...
*** ERROR *** table-prior returns NAN. Argument is -56.1796 but prior is defined on [-16,16] only.
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 help; please contact the developers at <[email protected]>.
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment