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INLA-Pardiso

fernandomayer
Jun 20th, 2024 (edited)
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  1.     Read ntt 16 1 with max.threads 16
  2.     Found num.threads = 16:1 max_threads = 16
  3.  
  4.     39a87469400fa169507c508366eca6ae7588cfdf - Wed Jun 19 21:58:47 2024 +0900
  5. Report bugs to <help@r-inla.org>
  6. Set reordering to id=[0] and name=[default]
  7. Process file[/tmp/RtmpgL4Rpb/filed61f43ace347/Model.ini] threads[16] max.threads[16] blas_threads[1] nested[16:1]
  8. inla_build...
  9.     number of sections=[10]
  10.     parse section=[0] name=[INLA.libR] type=[LIBR]
  11.     inla_parse_libR...
  12.         section[INLA.libR]
  13.             R_HOME=[/usr/local/lib64/R]
  14.     parse section=[7] name=[INLA.Expert] type=[EXPERT]
  15.     inla_parse_expert...
  16.         section[INLA.Expert]
  17.             disable.gaussian.check=[0]
  18.             Measure dot.product.gain=[No]
  19.             cpo.manual=[0]
  20.             jp.file=[(null)]
  21.             jp.model=[(null)]
  22.     parse section=[1] name=[INLA.Model] type=[PROBLEM]
  23.     inla_parse_problem...
  24.         name=[INLA.Model]
  25.         R-INLA version = [24.06.19]
  26.         R-INLA build date = [19893]
  27.         Build tag = [devel]
  28.         System memory = [31.0Gb]
  29.         Cores = (Physical= 16, Logical= 16)
  30.         'char' is signed
  31.         BUFSIZ is 8192
  32.         openmp.strategy=[default]
  33.         pardiso-library installed and working? = [yes]
  34.         smtp = [pardiso]
  35.         strategy = [pardiso]
  36.         store results in directory=[/tmp/RtmpgL4Rpb/filed61f43ace347/results.files]
  37.         output:
  38.             gcpo=[0]
  39.                 num.level.sets=[-1]
  40.                 size.max=[32]
  41.                 strategy=[Posterior]
  42.                 correct.hyperpar=[1]
  43.                 epsilon=[0.005]
  44.                 prior.diagonal=[0.0001]
  45.                 keep=[]
  46.                 remove.fixed=[1]
  47.                 remove=[]
  48.             cpo=[0]
  49.             po=[0]
  50.             dic=[0]
  51.             kld=[1]
  52.             mlik=[1]
  53.             q=[0]
  54.             graph=[0]
  55.             hyperparameters=[1]
  56.             config=[0]
  57.             config.lite=[0]
  58.             likelihood.info=[0]
  59.             internal.opt=[1]
  60.             save.memory=[0]
  61.             summary=[1]
  62.             return.marginals=[1]
  63.             return.marginals.predictor=[0]
  64.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  65.             ncdf=[0]  [ ]
  66.     parse section=[3] name=[Predictor] type=[PREDICTOR]
  67.     inla_parse_predictor ...
  68.         section=[Predictor]
  69.         dir=[predictor]
  70.         PRIOR->name=[loggamma]
  71.         hyperid=[53001|Predictor]
  72.         PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
  73.         PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
  74.         PRIOR->PARAMETERS=[1, 1e-05]
  75.         initialise log_precision[13.8155]
  76.         fixed=[1]
  77.         user.scale=[1]
  78.         n=[100]
  79.         m=[0]
  80.         ndata=[100]
  81.         compute=[1]
  82.         read offsets from file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1]
  83.         read n=[200] entries from file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1]
  84.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 0/100  (idx,y) = (0, 0)
  85.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 1/100  (idx,y) = (1, 0)
  86.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 2/100  (idx,y) = (2, 0)
  87.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 3/100  (idx,y) = (3, 0)
  88.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 4/100  (idx,y) = (4, 0)
  89.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 5/100  (idx,y) = (5, 0)
  90.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 6/100  (idx,y) = (6, 0)
  91.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 7/100  (idx,y) = (7, 0)
  92.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 8/100  (idx,y) = (8, 0)
  93.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61fb141df1] 9/100  (idx,y) = (9, 0)
  94.         A=[(null)]
  95.         Aext=[(null)]
  96.         AextPrecision=[1e+08]
  97.         output:
  98.             summary=[1]
  99.             return.marginals=[1]
  100.             return.marginals.predictor=[0]
  101.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  102.             ncdf=[0]  [ ]
  103.     parse section=[2] name=[INLA.Data1] type=[DATA]
  104.     inla_parse_data [section 1]...
  105.         tag=[INLA.Data1]
  106.         family=[GAUSSIAN]
  107.         likelihood=[GAUSSIAN]
  108.         file->name=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7987822a]
  109.         file->name=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f271dea56]
  110.         file->name=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f1dab05d2]
  111.         file->name=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f5a1ca77b]
  112.         read n=[300] entries from file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7987822a]
  113.             0/100  (idx,a,y,d) = (0, 1, -0.215721, 1)
  114.             1/100  (idx,a,y,d) = (1, 1, 0.616893, 1)
  115.             2/100  (idx,a,y,d) = (2, 1, -1.54725, 1)
  116.             3/100  (idx,a,y,d) = (3, 1, -0.191393, 1)
  117.             4/100  (idx,a,y,d) = (4, 1, -0.843107, 1)
  118.             5/100  (idx,a,y,d) = (5, 1, 3.12849, 1)
  119.             6/100  (idx,a,y,d) = (6, 1, 1.21092, 1)
  120.             7/100  (idx,a,y,d) = (7, 1, -1.07349, 1)
  121.             8/100  (idx,a,y,d) = (8, 1, 2.64234, 1)
  122.             9/100  (idx,a,y,d) = (9, 1, 1.92614, 1)
  123.         likelihood.variant=[0]
  124.         initialise log_precision[4]
  125.         fixed0=[0]
  126.         PRIOR0->name=[loggamma]
  127.         hyperid=[65001|INLA.Data1]
  128.         PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
  129.         PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
  130.         PRIOR0->PARAMETERS0=[1, 5e-05]
  131.         initialise log_precision offset[72.0873]
  132.         fixed1=[1]
  133.         PRIOR1->name=[none]
  134.         hyperid=[65002|INLA.Data1]
  135.         PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
  136.         PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
  137.         PRIOR1->PARAMETERS1=[]
  138.         Link model   [IDENTITY]
  139.         Link order   [-1]
  140.         Link variant [-1]
  141.         Link a       [1]
  142.         Link ntheta  [0]
  143.         mix.use[0]
  144.     section=[4] name=[(Intercept)] type=[LINEAR]
  145.     inla_parse_linear...
  146.         section[(Intercept)]
  147.         dir=[fixed.effect00000001]
  148.         file for covariates=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89]
  149.         read n=[200] entries from file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89]
  150.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 0/100  (idx,y) = (0, 1)
  151.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 1/100  (idx,y) = (1, 1)
  152.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 2/100  (idx,y) = (2, 1)
  153.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 3/100  (idx,y) = (3, 1)
  154.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 4/100  (idx,y) = (4, 1)
  155.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 5/100  (idx,y) = (5, 1)
  156.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 6/100  (idx,y) = (6, 1)
  157.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 7/100  (idx,y) = (7, 1)
  158.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 8/100  (idx,y) = (8, 1)
  159.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f7ceb5b89] 9/100  (idx,y) = (9, 1)
  160.         prior mean=[0]
  161.         prior precision=[0]
  162.         compute=[1]
  163.         output:
  164.             summary=[1]
  165.             return.marginals=[1]
  166.             return.marginals.predictor=[0]
  167.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  168.             ncdf=[0]  [ ]
  169.     section=[5] name=[z] type=[LINEAR]
  170.     inla_parse_linear...
  171.         section[z]
  172.         dir=[fixed.effect00000002]
  173.         file for covariates=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25]
  174.         read n=[200] entries from file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25]
  175.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 0/100  (idx,y) = (0, -1.06742)
  176.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 1/100  (idx,y) = (1, -0.377457)
  177.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 2/100  (idx,y) = (2, -2.50092)
  178.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 3/100  (idx,y) = (3, -1.2)
  179.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 4/100  (idx,y) = (4, -1.80372)
  180.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 5/100  (idx,y) = (5, 2.1775)
  181.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 6/100  (idx,y) = (6, 0.281688)
  182.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 7/100  (idx,y) = (7, -2.0705)
  183.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 8/100  (idx,y) = (8, 1.56291)
  184.         file=[/tmp/RtmpgL4Rpb/filed61f43ace347/data.files/filed61f484a5e25] 9/100  (idx,y) = (9, 0.93087)
  185.         prior mean=[0]
  186.         prior precision=[0.001]
  187.         compute=[1]
  188.         output:
  189.             summary=[1]
  190.             return.marginals=[1]
  191.             return.marginals.predictor=[0]
  192.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  193.             ncdf=[0]  [ ]
  194.     parse section=[9] name=[INLA.pardiso] type=[PARDISO]
  195.     inla_parse_pardiso...
  196.         section[INLA.pardiso]
  197.         verbose[0]
  198.         debug[0]
  199.         parallel.reordering[1]
  200.         nrhs[-1]
  201.     parse section=[8] name=[INLA.lp.scale] type=[LP.SCALE]
  202.     inla_parse_lp_scale...
  203.         section[INLA.lp.scale]
  204.  
  205.     Index table: number of entries[3], total length[102]
  206.         tag                            start-index     length
  207.         Predictor                               0        100
  208.         (Intercept)                           100          1
  209.         z                                     101          1
  210.     List of hyperparameters:
  211.         theta[0] = [Log precision for the Gaussian observations]
  212.  
  213.     parse section=[6] name=[INLA.Parameters] type=[INLA]
  214.     inla_parse_INLA...
  215.         section[INLA.Parameters]
  216.             lincomb.derived.correlation.matrix = [No]
  217.         global_node.factor = 2.000
  218.         global_node.degree = 2147483647
  219.         reordering = -1
  220.         constr.marginal.diagonal = 1.49e-08
  221. Contents of ai_param 0x557f7a874230
  222.     Optimiser: DEFAULT METHOD
  223.         Option for GSL-BFGS2: tol  = 0.1
  224.         Option for GSL-BFGS2: step_size = 1
  225.         Option for GSL-BFGS2: epsx = 0.001
  226.         Option for GSL-BFGS2: epsf = 0.002
  227.         Option for GSL-BFGS2: epsg = 0.005
  228.         Restart: 0
  229.         Optimise: try to be smart: Yes
  230.         Optimise: use directions: Yes
  231.         Mode restart: Yes
  232.         Mode fixed: No
  233.         Mode use_mode: No
  234.         parallel linesearch [0]
  235.     Gaussian approximation:
  236.         tolerance_func = 0.002
  237.         tolerance_step = 5e-06
  238.         optpar_fp = 0
  239.         optpar_nr_step_factor = -0.1
  240.     Gaussian data: Yes
  241.     Strategy:   Use a mean-skew corrected Gaussian by fitting a Skew-Normal
  242.     Fast mode:  On
  243.     Use linear approximation to log(|Q +c|)? Yes
  244.         Method:  Compute the derivative exact
  245.     Parameters for improved approximations
  246.         Number of points evaluate:   9
  247.         Step length to compute derivatives numerically:  0.0001
  248.         Stencil to compute derivatives numerically:  5
  249.         Cutoff value to construct local neigborhood:     0.0001
  250.     Log calculations:    On
  251.     Log calculated marginal for the hyperparameters:     On
  252.     Integration strategy:    Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
  253.         f0 (CCD only):   1.100
  254.         dz (GRID only):  0.750
  255.         Adjust weights (GRID only):  On
  256.         Difference in log-density limit (GRID only):     6.000
  257.         Skip configurations with (presumed) small density (GRID only):   On
  258.     Gradient is computed using Central difference with step-length 0.005000
  259.     Hessian is computed using Central difference with step-length 0.070711
  260.     Hessian matrix is forced to be a diagonal matrix? [No]
  261.     Compute effective number of parameters? [Yes]
  262.     Perform a Monte Carlo error-test? [No]
  263.     Interpolator [Auto]
  264.     CPO required diff in log-density [3]
  265.     Stupid search mode:
  266.         Status     [On]
  267.         Max iter   [1000]
  268.         Factor     [1.05]
  269.     Numerical integration of hyperparameters:
  270.         Maximum number of function evaluations [100000]
  271.         Relative error ....................... [1e-05]
  272.         Absolute error ....................... [1e-06]
  273.     To stabilise the numerical optimisation:
  274.         Minimum value of the -Hessian [-inf]
  275.         Strategy for the linear term [Keep]
  276.     CPO manual calculation[No]
  277.     VB correction is [Enabled]
  278.         strategy                    = [mean]
  279.         verbose                     = [Yes]
  280.         f_enable_limit_mean         = [30]
  281.         f_enable_limit_var          = [25]
  282.         f_enable_limit_mean_max     = [1024]
  283.         f_enable_limit_variance_max = [768]
  284.         iter_max                    = [25]
  285.         emergency                   = [25.00]
  286.         hessian_update              = [2]
  287.         hessian_strategy            = [full]
  288.     Misc options:
  289.         Hessian correct skewness only [1]
  290. inla_build: check for unused entries in[/tmp/RtmpgL4Rpb/filed61f43ace347/Model.ini]
  291. inla_INLA_preopt_experimental...
  292.     Mode....................... [Compact]
  293.     Setup...................... [0.01s]
  294.     Sparse-matrix library...... [pardiso]
  295.     OpenMP strategy............ [pardiso]
  296.     num.threads................ [16:1]
  297.     blas.num.threads........... [1]
  298.     Density-strategy........... [High]
  299.     Size of graph.............. [2]
  300.     Number of constraints...... [0]
  301.     Optimizing sort2_id........ [280]
  302.     Optimizing sort2_dd........ [329]
  303.     Optimizing Qx-strategy..... serial[0.312] parallel [0.688] choose[serial]
  304.     Optimizing pred-strategy... plain [0.641] data-rich[0.359] choose[data-rich]
  305.  
  306.     List of hyperparameters:
  307.         theta[0] = [Log precision for the Gaussian observations]
  308.  
  309.  
  310. Compute initial values...
  311.     Iter[0] RMS(err) = 1.000, update with step-size = 0.898
  312.     Iter[1] RMS(err) = 0.082, update with step-size = 1.152
  313.     Iter[2] RMS(err) = 0.995, update with step-size = 0.796
  314.     Initial values computed in 0.0007 seconds
  315.         x[0] = 0.8330
  316.         x[1] = 0.8439
  317.         x[0] = 0.8330
  318.         x[1] = 0.8439
  319.  
  320. Optimise using DEFAULT METHOD
  321. Smart optimise part I: estimate gradient using forward differences
  322. malloc(): invalid size (unsorted)
  323. munmap_chunk(): invalid pointer
  324.  
  325.  *** inla.core.safe:  The inla program failed, but will rerun in case better initial values may help. try=1/1
  326.     Read ntt 16 1 with max.threads 16
  327.     Found num.threads = 16:1 max_threads = 16
  328.  
  329.     39a87469400fa169507c508366eca6ae7588cfdf - Wed Jun 19 21:58:47 2024 +0900
  330. Report bugs to <help@r-inla.org>
  331. Set reordering to id=[0] and name=[default]
  332. Process file[/tmp/RtmpgL4Rpb/filed61f44f97526/Model.ini] threads[16] max.threads[16] blas_threads[1] nested[16:1]
  333. inla_build...
  334.     number of sections=[10]
  335.     parse section=[0] name=[INLA.libR] type=[LIBR]
  336.     inla_parse_libR...
  337.         section[INLA.libR]
  338.             R_HOME=[/usr/local/lib64/R]
  339.     parse section=[7] name=[INLA.Expert] type=[EXPERT]
  340.     inla_parse_expert...
  341.         section[INLA.Expert]
  342.             disable.gaussian.check=[0]
  343.             Measure dot.product.gain=[No]
  344.             cpo.manual=[0]
  345.             jp.file=[(null)]
  346.             jp.model=[(null)]
  347.     parse section=[1] name=[INLA.Model] type=[PROBLEM]
  348.     inla_parse_problem...
  349.         name=[INLA.Model]
  350.         R-INLA version = [24.06.19]
  351.         R-INLA build date = [19893]
  352.         Build tag = [devel]
  353.         System memory = [31.0Gb]
  354.         Cores = (Physical= 16, Logical= 16)
  355.         'char' is signed
  356.         BUFSIZ is 8192
  357.         openmp.strategy=[default]
  358.         pardiso-library installed and working? = [yes]
  359.         smtp = [pardiso]
  360.         strategy = [pardiso]
  361.         store results in directory=[/tmp/RtmpgL4Rpb/filed61f44f97526/results.files]
  362.         output:
  363.             gcpo=[0]
  364.                 num.level.sets=[-1]
  365.                 size.max=[32]
  366.                 strategy=[Posterior]
  367.                 correct.hyperpar=[1]
  368.                 epsilon=[0.005]
  369.                 prior.diagonal=[0.0001]
  370.                 keep=[]
  371.                 remove.fixed=[1]
  372.                 remove=[]
  373.             cpo=[0]
  374.             po=[0]
  375.             dic=[0]
  376.             kld=[1]
  377.             mlik=[1]
  378.             q=[0]
  379.             graph=[0]
  380.             hyperparameters=[1]
  381.             config=[0]
  382.             config.lite=[0]
  383.             likelihood.info=[0]
  384.             internal.opt=[1]
  385.             save.memory=[0]
  386.             summary=[1]
  387.             return.marginals=[0]
  388.             return.marginals.predictor=[0]
  389.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  390.             ncdf=[0]  [ ]
  391.     parse section=[3] name=[Predictor] type=[PREDICTOR]
  392.     inla_parse_predictor ...
  393.         section=[Predictor]
  394.         dir=[predictor]
  395.         PRIOR->name=[loggamma]
  396.         hyperid=[53001|Predictor]
  397.         PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
  398.         PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
  399.         PRIOR->PARAMETERS=[1, 1e-05]
  400.         initialise log_precision[13.8155]
  401.         fixed=[1]
  402.         user.scale=[1]
  403.         n=[100]
  404.         m=[0]
  405.         ndata=[100]
  406.         compute=[0]
  407.         read offsets from file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e]
  408.         read n=[200] entries from file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e]
  409.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 0/100  (idx,y) = (0, 0)
  410.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 1/100  (idx,y) = (1, 0)
  411.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 2/100  (idx,y) = (2, 0)
  412.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 3/100  (idx,y) = (3, 0)
  413.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 4/100  (idx,y) = (4, 0)
  414.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 5/100  (idx,y) = (5, 0)
  415.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 6/100  (idx,y) = (6, 0)
  416.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 7/100  (idx,y) = (7, 0)
  417.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 8/100  (idx,y) = (8, 0)
  418.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f1a1fff6e] 9/100  (idx,y) = (9, 0)
  419.         A=[(null)]
  420.         Aext=[(null)]
  421.         AextPrecision=[1e+08]
  422.         output:
  423.             summary=[1]
  424.             return.marginals=[0]
  425.             return.marginals.predictor=[0]
  426.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  427.             ncdf=[0]  [ ]
  428.     parse section=[2] name=[INLA.Data1] type=[DATA]
  429.     inla_parse_data [section 1]...
  430.         tag=[INLA.Data1]
  431.         family=[GAUSSIAN]
  432.         likelihood=[GAUSSIAN]
  433.         file->name=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f3345925e]
  434.         file->name=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f6c5a1b4a]
  435.         file->name=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f469a16f5]
  436.         file->name=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f26989c6c]
  437.         read n=[300] entries from file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f3345925e]
  438.             0/100  (idx,a,y,d) = (0, 1, -0.215721, 1)
  439.             1/100  (idx,a,y,d) = (1, 1, 0.616893, 1)
  440.             2/100  (idx,a,y,d) = (2, 1, -1.54725, 1)
  441.             3/100  (idx,a,y,d) = (3, 1, -0.191393, 1)
  442.             4/100  (idx,a,y,d) = (4, 1, -0.843107, 1)
  443.             5/100  (idx,a,y,d) = (5, 1, 3.12849, 1)
  444.             6/100  (idx,a,y,d) = (6, 1, 1.21092, 1)
  445.             7/100  (idx,a,y,d) = (7, 1, -1.07349, 1)
  446.             8/100  (idx,a,y,d) = (8, 1, 2.64234, 1)
  447.             9/100  (idx,a,y,d) = (9, 1, 1.92614, 1)
  448.         likelihood.variant=[0]
  449.         initialise log_precision[4]
  450.         fixed0=[0]
  451.         PRIOR0->name=[loggamma]
  452.         hyperid=[65001|INLA.Data1]
  453.         PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
  454.         PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
  455.         PRIOR0->PARAMETERS0=[1, 5e-05]
  456.         initialise log_precision offset[72.0873]
  457.         fixed1=[1]
  458.         PRIOR1->name=[none]
  459.         hyperid=[65002|INLA.Data1]
  460.         PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
  461.         PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
  462.         PRIOR1->PARAMETERS1=[]
  463.         Link model   [IDENTITY]
  464.         Link order   [-1]
  465.         Link variant [-1]
  466.         Link a       [1]
  467.         Link ntheta  [0]
  468.         mix.use[0]
  469.     section=[4] name=[(Intercept)] type=[LINEAR]
  470.     inla_parse_linear...
  471.         section[(Intercept)]
  472.         dir=[fixed.effect00000001]
  473.         file for covariates=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553]
  474.         read n=[200] entries from file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553]
  475.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 0/100  (idx,y) = (0, 1)
  476.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 1/100  (idx,y) = (1, 1)
  477.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 2/100  (idx,y) = (2, 1)
  478.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 3/100  (idx,y) = (3, 1)
  479.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 4/100  (idx,y) = (4, 1)
  480.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 5/100  (idx,y) = (5, 1)
  481.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 6/100  (idx,y) = (6, 1)
  482.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 7/100  (idx,y) = (7, 1)
  483.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 8/100  (idx,y) = (8, 1)
  484.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f357df553] 9/100  (idx,y) = (9, 1)
  485.         prior mean=[0]
  486.         prior precision=[0]
  487.         compute=[1]
  488.         output:
  489.             summary=[1]
  490.             return.marginals=[0]
  491.             return.marginals.predictor=[0]
  492.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  493.             ncdf=[0]  [ ]
  494.     section=[5] name=[z] type=[LINEAR]
  495.     inla_parse_linear...
  496.         section[z]
  497.         dir=[fixed.effect00000002]
  498.         file for covariates=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584]
  499.         read n=[200] entries from file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584]
  500.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 0/100  (idx,y) = (0, -1.06742)
  501.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 1/100  (idx,y) = (1, -0.377457)
  502.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 2/100  (idx,y) = (2, -2.50092)
  503.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 3/100  (idx,y) = (3, -1.2)
  504.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 4/100  (idx,y) = (4, -1.80372)
  505.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 5/100  (idx,y) = (5, 2.1775)
  506.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 6/100  (idx,y) = (6, 0.281688)
  507.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 7/100  (idx,y) = (7, -2.0705)
  508.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 8/100  (idx,y) = (8, 1.56291)
  509.         file=[/tmp/RtmpgL4Rpb/filed61f44f97526/data.files/filed61f69667584] 9/100  (idx,y) = (9, 0.93087)
  510.         prior mean=[0]
  511.         prior precision=[0.001]
  512.         compute=[1]
  513.         output:
  514.             summary=[1]
  515.             return.marginals=[0]
  516.             return.marginals.predictor=[0]
  517.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  518.             ncdf=[0]  [ ]
  519.     parse section=[9] name=[INLA.pardiso] type=[PARDISO]
  520.     inla_parse_pardiso...
  521.         section[INLA.pardiso]
  522.         verbose[0]
  523.         debug[0]
  524.         parallel.reordering[1]
  525.         nrhs[-1]
  526.     parse section=[8] name=[INLA.lp.scale] type=[LP.SCALE]
  527.     inla_parse_lp_scale...
  528.         section[INLA.lp.scale]
  529.  
  530.     Index table: number of entries[3], total length[102]
  531.         tag                            start-index     length
  532.         Predictor                               0        100
  533.         (Intercept)                           100          1
  534.         z                                     101          1
  535.     List of hyperparameters:
  536.         theta[0] = [Log precision for the Gaussian observations]
  537.  
  538.     parse section=[6] name=[INLA.Parameters] type=[INLA]
  539.     inla_parse_INLA...
  540.         section[INLA.Parameters]
  541.             lincomb.derived.correlation.matrix = [No]
  542.         global_node.factor = 2.000
  543.         global_node.degree = 2147483647
  544.         reordering = -1
  545.         constr.marginal.diagonal = 1.49e-08
  546. Contents of ai_param 0x6448e92ba230
  547.     Optimiser: DEFAULT METHOD
  548.         Option for GSL-BFGS2: tol  = 0.1
  549.         Option for GSL-BFGS2: step_size = 1
  550.         Option for GSL-BFGS2: epsx = 0.002
  551.         Option for GSL-BFGS2: epsf = 0.004
  552.         Option for GSL-BFGS2: epsg = 0.01
  553.         Restart: 0
  554.         Optimise: try to be smart: No
  555.         Optimise: use directions: Yes
  556.         Mode restart: Yes
  557.         Mode fixed: No
  558.         Mode use_mode: No
  559.         parallel linesearch [0]
  560.     Gaussian approximation:
  561.         tolerance_func = 0.004
  562.         tolerance_step = 1e-05
  563.         optpar_fp = 0
  564.         optpar_nr_step_factor = -0.1
  565.     Gaussian data: Yes
  566.     Strategy:   Use the Gaussian approximation
  567.     Fast mode:  On
  568.     Use linear approximation to log(|Q +c|)? Yes
  569.         Method:  Compute the derivative exact
  570.     Parameters for improved approximations
  571.         Number of points evaluate:   9
  572.         Step length to compute derivatives numerically:  0.0001
  573.         Stencil to compute derivatives numerically:  5
  574.         Cutoff value to construct local neigborhood:     0.0001
  575.     Log calculations:    On
  576.     Log calculated marginal for the hyperparameters:     On
  577.     Integration strategy:    Use only the modal configuration (EMPIRICAL_BAYES)
  578.         f0 (CCD only):   1.100
  579.         dz (GRID only):  0.750
  580.         Adjust weights (GRID only):  On
  581.         Difference in log-density limit (GRID only):     6.000
  582.         Skip configurations with (presumed) small density (GRID only):   On
  583.     Gradient is computed using Central difference with step-length 0.005000
  584.     Hessian is computed using Central difference with step-length 0.070711
  585.     Hessian matrix is forced to be a diagonal matrix? [Yes]
  586.     Compute effective number of parameters? [Yes]
  587.     Perform a Monte Carlo error-test? [No]
  588.     Interpolator [Auto]
  589.     CPO required diff in log-density [3]
  590.     Stupid search mode:
  591.         Status     [On]
  592.         Max iter   [1000]
  593.         Factor     [1.05]
  594.     Numerical integration of hyperparameters:
  595.         Maximum number of function evaluations [100000]
  596.         Relative error ....................... [1e-05]
  597.         Absolute error ....................... [1e-06]
  598.     To stabilise the numerical optimisation:
  599.         Minimum value of the -Hessian [inf]
  600.         Strategy for the linear term [Keep]
  601.     CPO manual calculation[No]
  602.     VB-correction is [Disabled]
  603.     Misc options:
  604.         Hessian correct skewness only [1]
  605. inla_build: check for unused entries in[/tmp/RtmpgL4Rpb/filed61f44f97526/Model.ini]
  606. inla_INLA_preopt_experimental...
  607.     Mode....................... [Compact]
  608.     Setup...................... [0.01s]
  609.     Sparse-matrix library...... [pardiso]
  610.     OpenMP strategy............ [pardiso]
  611.     num.threads................ [16:1]
  612.     blas.num.threads........... [1]
  613.     Density-strategy........... [High]
  614.     Size of graph.............. [2]
  615.     Number of constraints...... [0]
  616.     Optimizing sort2_id........ [280]
  617.     Optimizing sort2_dd........ [316]
  618.     Optimizing Qx-strategy..... serial[0.332] parallel [0.668] choose[serial]
  619.     Optimizing pred-strategy... plain [0.632] data-rich[0.368] choose[data-rich]
  620.  
  621.     List of hyperparameters:
  622.         theta[0] = [Log precision for the Gaussian observations]
  623.  
  624.  
  625. Compute initial values...
  626.     Iter[0] RMS(err) = 1.000, update with step-size = 0.898
  627.     Iter[1] RMS(err) = 0.082, update with step-size = 1.152
  628.     Iter[2] RMS(err) = 0.995, update with step-size = 0.796
  629.     Initial values computed in 0.0005 seconds
  630.         x[0] = 0.8330
  631.         x[1] = 0.8439
  632.         x[0] = 0.8330
  633.         x[1] = 0.8439
  634.  
  635. Optimise using DEFAULT METHOD
  636. malloc(): invalid size (unsorted)
  637. Error in inla.core.safe(formula = formula, family = family, contrasts = contrasts,  :
  638.   The inla-program exited with an error. Unless you interupted it yourself, please rerun with verbose=TRUE and check the output carefully.
  639.   If this does not help, please contact the developers at <help@r-inla.org>.
  640. The inla program failed and the maximum number of tries has been reached.
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