CONTAINS Runtime Modules of Parallel Sparse Linear Solver PARDISO Vers. 7.0
CUSTOMIZED FOR THE R-INLA PACKAGE WHICH SOLVES A LARGE CLASS OF STATISTICAL
Copyright Universita della Svizzera italiana 2000-2020 All Rights Reserved.
No PARDISO license file found.  Please see `http://www.pardiso-project.org/r-inla
where to place the license file pardiso.lic
Set reordering to id=[0] and name=[default]
Process file[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/Model.ini] threads[4] max.threads[4] blas_threads[1] nested[4:1]
R-INLA build date=[Mon Feb 22 11:58:09 PM +03 2021]
pardiso-library installed and working? = [no]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
read n=[296] entries from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9]
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 0/148  (idx,y) = (0, 6.85616)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 1/148  (idx,y) = (1, 7.16781)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 2/148  (idx,y) = (2, 7.29702)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 3/148  (idx,y) = (3, 7.57281)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 4/148  (idx,y) = (4, 7.02316)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 5/148  (idx,y) = (5, 7.11684)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 6/148  (idx,y) = (6, 7.64876)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 7/148  (idx,y) = (7, 7.16448)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 8/148  (idx,y) = (8, 7.28035)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3a4ee9b9] 9/148  (idx,y) = (9, 7.75642)
read n=[444] entries from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e54691c68]
PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)/(1 + exp(x))]
PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x/(1 - x))]
read n=[296] entries from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33]
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 0/148  (idx,y) = (0, 0)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 1/148  (idx,y) = (1, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 2/148  (idx,y) = (2, 2)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 3/148  (idx,y) = (3, 3)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 4/148  (idx,y) = (4, 4)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 5/148  (idx,y) = (5, 5)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 6/148  (idx,y) = (6, 6)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 7/148  (idx,y) = (7, 7)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 8/148  (idx,y) = (8, 8)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e61950d33] 9/148  (idx,y) = (9, 9)
read extra constraint from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e95c152]
read n=[296] entries from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97]
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 0/148  (idx,y) = (0, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 1/148  (idx,y) = (1, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 2/148  (idx,y) = (2, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 3/148  (idx,y) = (3, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 4/148  (idx,y) = (4, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 5/148  (idx,y) = (5, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 6/148  (idx,y) = (6, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 7/148  (idx,y) = (7, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 8/148  (idx,y) = (8, 1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e12d28e97] 9/148  (idx,y) = (9, 1)
read n=[296] entries from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528]
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 0/148  (idx,y) = (0, 2.3)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 1/148  (idx,y) = (1, 11.8)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 2/148  (idx,y) = (2, 1.5)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 3/148  (idx,y) = (3, 5.4)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 4/148  (idx,y) = (4, 3.8)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 5/148  (idx,y) = (5, 2.2)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 6/148  (idx,y) = (6, 4.1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 7/148  (idx,y) = (7, 30.8)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 8/148  (idx,y) = (8, 3.3)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e3d8f6528] 9/148  (idx,y) = (9, 5.9)
read n=[296] entries from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab]
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 0/148  (idx,y) = (0, 7.1555)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 1/148  (idx,y) = (1, 7.62744)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 2/148  (idx,y) = (2, 7.07918)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 3/148  (idx,y) = (3, 7.25424)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 4/148  (idx,y) = (4, 6.78316)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 5/148  (idx,y) = (5, 8.56466)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 6/148  (idx,y) = (6, 8.16749)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 7/148  (idx,y) = (7, 7.12616)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 8/148  (idx,y) = (8, 7.04575)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e113a44ab] 9/148  (idx,y) = (9, 9.37889)
read n=[296] entries from file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63]
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 0/148  (idx,y) = (0, 6.3)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 1/148  (idx,y) = (1, 4.6)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 2/148  (idx,y) = (2, 3.7)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 3/148  (idx,y) = (3, 3.2)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 4/148  (idx,y) = (4, 3.5)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 5/148  (idx,y) = (5, 3.8)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 6/148  (idx,y) = (6, 2.1)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 7/148  (idx,y) = (7, 2.9)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 8/148  (idx,y) = (8, 4.5)
file=[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/data.files/file15b0e8723f63] 9/148  (idx,y) = (9, 3.7)
Index table: number of entries[6], total length[448]
Strategy:         Use a mean-skew corrected Gaussian by fitting a Skew-Normal
Use linear approximation to log(|Q +c|)? Yes
Method:         Compute the derivative exact
Step length to compute derivatives numerically:         0.000100002
Stencil to compute derivatives numerically:         5
Cutoff value to construct local neigborhood:         0.0001
Log calculated marginal for the hyperparameters:         On
Integration strategy:         Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
Difference in log-density limit (GRID only):         6.000
Skip configurations with (presumed) small density (GRID only):         On
Gradient is computed using Central difference with step-length 0.005000
Hessian is computed using Central difference with step-length 0.070711
Hessian matrix is forced to be a diagonal matrix? [No]
Compute effective number of parameters? [Yes]
Maximum number of function evaluations [100000]
To stabilise the numerical optimisation:
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inla_build: check for unused entries in[/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/Model.ini]
Found optimal reordering=[metis] nnz(L)=[3112] and use_global_nodes(user)=[no]
theta[0] = [Log precision for region.indexS]
theta[1] = [Logit phi for region.indexS]
Smart optimise part I: estimate gradient using forward differences
Iter=4 |grad|=0.257 |x-x.old|=0.122 |f-f.old|=0.048 Reached numerical limit!
Smart optimise part II: estimate gradient using central differences
Smart optimise part II: restart optimiser
Optim: Number of function evaluations = 116
Compute the Hessian using central differences and step_size[0.0707107]. Matrix-type [dense]
Smart optimise part III: estimate Hessian using forward differences
Smart optimise part III: Hessian seems fine, keep it
StDev/Correlation matrix (scaled inverse Hessian)
Compute corrected stdev for theta[0]: negative 1.037  positive 0.961
Compute corrected stdev for theta[1]: negative 0.842  positive 1.344
config  0=[ -1  0] log(rel.dens)= -0.275, accept, compute, 0.00s
config  1=[ -2  0] log(rel.dens)= -1.066, accept, compute, 0.00s
config  2=[ -3  0] log(rel.dens)= -2.332, accept, compute, 0.00s
config  3=[ -4  0] log(rel.dens)= -4.033, accept, compute, 0.01s
config  4=[ -5  0] log(rel.dens)= -6.133, diff to large, stop searching
config  5=[  1  0] log(rel.dens)= -0.289, accept, compute, 0.00s
config  6=[  2  0] log(rel.dens)= -1.193, accept, compute, 0.01s
config  7=[  3  0] log(rel.dens)= -2.766, accept, compute, 0.01s
config  8=[  4  0] log(rel.dens)= -5.069, accept, compute, 0.00s
config  9=[  5  0] log(rel.dens)= -8.166, diff to large, stop searching
config 10=[  0 -1] log(rel.dens)= -0.321, accept, compute, 0.00s
config 11=[  0 -2] log(rel.dens)= -1.465, accept, compute, 0.00s
config 12=[  0 -3] log(rel.dens)= -3.706, accept, compute, 0.00s
config 13=[  0 -4] log(rel.dens)= -7.263, diff to large, stop searching
config 14=[  0  1] log(rel.dens)= -0.215, accept, compute, 0.00s
config 15=[  0  2] log(rel.dens)= -0.710, accept, compute, 0.01s
config 16=[  0  3] log(rel.dens)= -1.320, accept, compute, 0.00s
config 17=[  0  4] log(rel.dens)= -1.980, accept, compute, 0.01s
config 18=[  0  5] log(rel.dens)= -2.639, accept, compute, 0.00s
config 19=[  0  6] log(rel.dens)= -3.334, accept, compute, 0.00s
config 20=[  0  7] log(rel.dens)= -4.045, accept, compute, 0.01s
config 21=[  0  8] log(rel.dens)= -4.799, accept, compute, 0.00s
config 22=[  0  9] log(rel.dens)= -5.598, accept, compute, 0.00s
config 23=[  0 10] log(rel.dens)= -6.442, diff to large, stop searching
config 24=[  0  0] log(rel.dens)= -0.000, accept, compute, 0.01s
config 25=[  1  1] log(rel.dens)= -0.499, accept, compute, 0.01s
config 26=[  1  2] log(rel.dens)= -0.938, accept, compute, 0.00s
config 27=[  1  3] log(rel.dens)= -1.440, accept, compute, 0.01s
config 28=[  1  4] log(rel.dens)= -1.949, accept, compute, 0.00s
config 29=[  1  5] log(rel.dens)= -2.425, accept, compute, 0.01s
config 30=[  1  6] log(rel.dens)= -2.917, accept, compute, 0.00s
config 31=[  1  7] log(rel.dens)= -3.414, accept, compute, 0.00s
config 32=[  1  8] log(rel.dens)= -3.951, accept, compute, 0.01s
config 33=[  1  9] log(rel.dens)= -4.532, accept, compute, 0.01s
config 34=[  1 -1] log(rel.dens)= -0.583, accept, compute, 0.00s
config 35=[  1 -2] log(rel.dens)= -1.706, accept, compute, 0.00s
config 36=[  1 -3] log(rel.dens)= -3.982, accept, compute, 0.01s
config 37=[  2  1] log(rel.dens)= -1.393, accept, compute, 0.01s
config 38=[  2  2] log(rel.dens)= -1.768, accept, compute, 0.01s
config 39=[  2  3] log(rel.dens)= -2.151, accept, compute, 0.01s
config 40=[  2  4] log(rel.dens)= -2.493, accept, compute, 0.00s
config 41=[  2  5] log(rel.dens)= -2.769, accept, compute, 0.01s
config 42=[  2  6] log(rel.dens)= -3.040, accept, compute, 0.00s
config 43=[  2  7] log(rel.dens)= -3.302, accept, compute, 0.00s
config 44=[  2  8] log(rel.dens)= -3.602, accept, compute, 0.00s
config 45=[  2  9] log(rel.dens)= -3.946, accept, compute, 0.00s
config 46=[  2 -1] log(rel.dens)= -1.460, accept, compute, 0.01s
config 47=[  2 -2] log(rel.dens)= -2.560, accept, compute, 0.00s
config 48=[  2 -3] log(rel.dens)= -4.873, accept, compute, 0.00s
config 49=[  3  1] log(rel.dens)= -2.953, accept, compute, 0.00s
config 50=[  3  2] log(rel.dens)= -3.255, accept, compute, 0.00s
config 51=[  3  3] log(rel.dens)= -3.506, accept, compute, 0.01s
config 52=[  3  4] log(rel.dens)= -3.664, accept, compute, 0.00s
config 53=[  3  5] log(rel.dens)= -3.720, accept, compute, 0.00s
config 54=[  3  6] log(rel.dens)= -3.748, accept, compute, 0.00s
config 55=[  3  7] log(rel.dens)= -3.756, accept, compute, 0.01s
config 56=[  3  8] log(rel.dens)= -3.797, accept, compute, 0.01s
config 57=[  3  9] log(rel.dens)= -3.882, accept, compute, 0.00s
config 58=[  3 -1] log(rel.dens)= -3.007, accept, compute, 0.00s
config 59=[  3 -2] log(rel.dens)= -4.083, accept, compute, 0.00s
config 60=[  3 -3] log(rel.dens)= -6.437, diff to large, stop and skip skip more distant configs
config 61=[  4  1] log(rel.dens)= -5.238, accept, compute, 0.01s
config 62=[  4  2] log(rel.dens)= -5.458, accept, compute, 0.00s
config 63=[  4  3] log(rel.dens)= -5.560, accept, compute, 0.00s
config 64=[  4  4] log(rel.dens)= -5.517, accept, compute, 0.00s
config 65=[  4  5] log(rel.dens)= -5.333, accept, compute, 0.01s
config 66=[  4  6] log(rel.dens)= -5.096, accept, compute, 0.00s
config 67=[  4  7] log(rel.dens)= -4.825, accept, compute, 0.00s
config 68=[  4  8] log(rel.dens)= -4.584, accept, compute, 0.00s
config 69=[  4  9] log(rel.dens)= -4.388, accept, compute, 0.00s
config 70=[  4 -1] log(rel.dens)= -5.284, accept, compute, 0.01s
config 71=[  4 -2] log(rel.dens)= -6.335, diff to large, stop and skip skip more distant configs
config 72=[ -1  1] log(rel.dens)= -0.492, accept, compute, 0.01s
config 73=[ -1  2] log(rel.dens)= -1.036, accept, compute, 0.00s
config 74=[ -1  3] log(rel.dens)= -1.742, accept, compute, 0.00s
config 75=[ -1  4] log(rel.dens)= -2.540, accept, compute, 0.01s
config 76=[ -1  5] log(rel.dens)= -3.365, accept, compute, 0.00s
config 77=[ -1  6] log(rel.dens)= -4.246, accept, compute, 0.00s
config 78=[ -1  7] log(rel.dens)= -5.153, accept, compute, 0.00s
config 79=[ -1  8] log(rel.dens)= -6.106, diff to large, stop and skip skip more distant configs
config 80=[ -1 -1] log(rel.dens)= -0.622, accept, compute, 0.01s
config 81=[ -1 -2] log(rel.dens)= -1.787, accept, compute, 0.00s
config 82=[ -1 -3] log(rel.dens)= -3.995, accept, compute, 0.00s
config 83=[ -2  1] log(rel.dens)= -1.284, accept, compute, 0.00s
config 84=[ -2  2] log(rel.dens)= -1.870, accept, compute, 0.00s
config 85=[ -2  3] log(rel.dens)= -2.662, accept, compute, 0.01s
config 86=[ -2  4] log(rel.dens)= -3.584, accept, compute, 0.00s
config 87=[ -2  5] log(rel.dens)= -4.562, accept, compute, 0.01s
config 88=[ -2  6] log(rel.dens)= -5.611, accept, compute, 0.01s
config 89=[ -2  7] log(rel.dens)= -6.698, diff to large, stop and skip skip more distant configs
config 90=[ -2 -1] log(rel.dens)= -1.440, accept, compute, 0.01s
config 91=[ -2 -2] log(rel.dens)= -2.625, accept, compute, 0.00s
config 92=[ -2 -3] log(rel.dens)= -4.803, accept, compute, 0.00s
config 93=[ -3  1] log(rel.dens)= -2.547, accept, compute, 0.01s
config 94=[ -3  2] log(rel.dens)= -3.170, accept, compute, 0.01s
config 95=[ -3  3] log(rel.dens)= -4.040, accept, compute, 0.00s
config 96=[ -3  4] log(rel.dens)= -5.074, accept, compute, 0.00s
config 97=[ -3  5] log(rel.dens)= -6.190, diff to large, stop and skip skip more distant configs
config 98=[ -3 -1] log(rel.dens)= -2.732, accept, compute, 0.00s
config 99=[ -3 -2] log(rel.dens)= -3.937, accept, compute, 0.00s
config 100=[ -3 -3] log(rel.dens)= -6.085, diff to large, stop and skip skip more distant configs
config 101=[ -4  1] log(rel.dens)= -4.244, accept, compute, 0.00s
config 102=[ -4  2] log(rel.dens)= -4.898, accept, compute, 0.00s
config 103=[ -4  3] log(rel.dens)= -5.836, accept, compute, 0.00s
config 104=[ -4  4] log(rel.dens)= -6.972, diff to large, stop and skip skip more distant configs
config 105=[ -4 -1] log(rel.dens)= -4.458, accept, compute, 0.00s
config 106=[ -4 -2] log(rel.dens)= -5.681, accept, compute, 0.01s
Combine the densities with relative weights:
Expected effective number of parameters: 146.626(0.164),  eqv.#replicates: 1.009
Marginal likelihood: Integration -1111.934 Gaussian-approx -1112.385
Compute the marginal for each of the 2 hyperparameters
Compute the marginal for theta[0] using numerical integration
Compute the marginal for theta[1] using numerical integration
Compute the marginal for the hyperparameters... done.
Wall-clock time used on [/private/var/folders/1s/zkmc02qn4k18r6jdtbb459hc0000gn/T/RtmpIjUAnP/file15b0e1d6316ba/Model.ini]
Number of fn-calls= 234 with 0.005 sec/fn-call
Parallel efficiency for 'Preparations' and 'Approx inference':
Accumulated CPU-time is equivalent to 1.02 threads running at 100%