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inla-manjaro

fernandomayer
Jun 25th, 2024
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  1. > n = 100; a = 1; b = 1; tau = 100
  2. > z = rnorm(n)
  3. > eta = a + b*z
  4. > scale = exp(rnorm(n))
  5. > prec = scale*tau
  6. > y = rnorm(n, mean = eta, sd = 1/sqrt(prec))
  7. > data = list(y=y, z=z)
  8. > formula = y ~ 1+z
  9. > result = inla(formula, family = "gaussian", data = data,
  10. +     verbose = TRUE)
  11.     Read ntt 16 1 with max.threads 16
  12.     Found num.threads = 16:1 max_threads = 16
  13.  
  14.     39a87469400fa169507c508366eca6ae7588cfdf - Wed Jun 19 21:58:47 2024 +0900
  15. Report bugs to <help@r-inla.org>
  16. Set reordering to id=[0] and name=[default]
  17. Process file[/tmp/RtmpfSOSbn/file585054fa8b4a/Model.ini] threads[16] max.threads[16] blas_threads[1] nested[16:1]
  18. inla_build...
  19.     number of sections=[10]
  20.     parse section=[0] name=[INLA.libR] type=[LIBR]
  21.     inla_parse_libR...
  22.         section[INLA.libR]
  23.             R_HOME=[/usr/local/lib64/R]
  24.     parse section=[7] name=[INLA.Expert] type=[EXPERT]
  25.     inla_parse_expert...
  26.         section[INLA.Expert]
  27.             disable.gaussian.check=[0]
  28.             Measure dot.product.gain=[No]
  29.             cpo.manual=[0]
  30.             jp.file=[(null)]
  31.             jp.model=[(null)]
  32.     parse section=[1] name=[INLA.Model] type=[PROBLEM]
  33.     inla_parse_problem...
  34.         name=[INLA.Model]
  35.         R-INLA version = [24.06.19]
  36.         R-INLA build date = [19893]
  37.         Build tag = [devel]
  38.         System memory = [31.0Gb]
  39.         Cores = (Physical= 16, Logical= 16)
  40.         'char' is signed
  41.         BUFSIZ is 8192
  42.         openmp.strategy=[default]
  43.         pardiso-library installed and working? = [yes]
  44.         smtp = [pardiso]
  45.         strategy = [pardiso]
  46.         store results in directory=[/tmp/RtmpfSOSbn/file585054fa8b4a/results.files]
  47.         output:
  48.             gcpo=[0]
  49.                 num.level.sets=[-1]
  50.                 size.max=[32]
  51.                 strategy=[Posterior]
  52.                 correct.hyperpar=[1]
  53.                 epsilon=[0.005]
  54.                 prior.diagonal=[0.0001]
  55.                 keep=[]
  56.                 remove.fixed=[1]
  57.                 remove=[]
  58.             cpo=[0]
  59.             po=[0]
  60.             dic=[0]
  61.             kld=[1]
  62.             mlik=[1]
  63.             q=[0]
  64.             graph=[0]
  65.             hyperparameters=[1]
  66.             config=[0]
  67.             config.lite=[0]
  68.             likelihood.info=[0]
  69.             internal.opt=[1]
  70.             save.memory=[0]
  71.             summary=[1]
  72.             return.marginals=[1]
  73.             return.marginals.predictor=[0]
  74.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  75.             ncdf=[0]  [ ]
  76.     parse section=[3] name=[Predictor] type=[PREDICTOR]
  77.     inla_parse_predictor ...
  78.         section=[Predictor]
  79.         dir=[predictor]
  80.         PRIOR->name=[loggamma]
  81.         hyperid=[53001|Predictor]
  82.         PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
  83.         PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
  84.         PRIOR->PARAMETERS=[1, 1e-05]
  85.         initialise log_precision[13.8155]
  86.         fixed=[1]
  87.         user.scale=[1]
  88.         n=[100]
  89.         m=[0]
  90.         ndata=[100]
  91.         compute=[1]
  92.         read offsets from file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb]
  93.         read n=[200] entries from file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb]
  94.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 0/100  (idx,y) = (0, 0)
  95.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 1/100  (idx,y) = (1, 0)
  96.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 2/100  (idx,y) = (2, 0)
  97.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 3/100  (idx,y) = (3, 0)
  98.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 4/100  (idx,y) = (4, 0)
  99.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 5/100  (idx,y) = (5, 0)
  100.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 6/100  (idx,y) = (6, 0)
  101.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 7/100  (idx,y) = (7, 0)
  102.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 8/100  (idx,y) = (8, 0)
  103.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58504034defb] 9/100  (idx,y) = (9, 0)
  104.         A=[(null)]
  105.         Aext=[(null)]
  106.         AextPrecision=[1e+08]
  107.         output:
  108.             summary=[1]
  109.             return.marginals=[1]
  110.             return.marginals.predictor=[0]
  111.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  112.             ncdf=[0]  [ ]
  113.     parse section=[2] name=[INLA.Data1] type=[DATA]
  114.     inla_parse_data [section 1]...
  115.         tag=[INLA.Data1]
  116.         family=[GAUSSIAN]
  117.         likelihood=[GAUSSIAN]
  118.         file->name=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file585074b6272f]
  119.         file->name=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850722482f1]
  120.         file->name=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506e197272]
  121.         file->name=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file585028bd4b9e]
  122.         read n=[300] entries from file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file585074b6272f]
  123.             0/100  (idx,a,y,d) = (0, 1, 0.539796, 1)
  124.             1/100  (idx,a,y,d) = (1, 1, 1.06761, 1)
  125.             2/100  (idx,a,y,d) = (2, 1, 1.43897, 1)
  126.             3/100  (idx,a,y,d) = (3, 1, 0.151292, 1)
  127.             4/100  (idx,a,y,d) = (4, 1, 1.32971, 1)
  128.             5/100  (idx,a,y,d) = (5, 1, 2.9832, 1)
  129.             6/100  (idx,a,y,d) = (6, 1, 1.28958, 1)
  130.             7/100  (idx,a,y,d) = (7, 1, -0.552891, 1)
  131.             8/100  (idx,a,y,d) = (8, 1, -0.735916, 1)
  132.             9/100  (idx,a,y,d) = (9, 1, -0.0893465, 1)
  133.         likelihood.variant=[0]
  134.         initialise log_precision[4]
  135.         fixed0=[0]
  136.         PRIOR0->name=[loggamma]
  137.         hyperid=[65001|INLA.Data1]
  138.         PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
  139.         PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
  140.         PRIOR0->PARAMETERS0=[1, 5e-05]
  141.         initialise log_precision offset[72.0873]
  142.         fixed1=[1]
  143.         PRIOR1->name=[none]
  144.         hyperid=[65002|INLA.Data1]
  145.         PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
  146.         PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
  147.         PRIOR1->PARAMETERS1=[]
  148.         Link model   [IDENTITY]
  149.         Link order   [-1]
  150.         Link variant [-1]
  151.         Link a       [1]
  152.         Link ntheta  [0]
  153.         mix.use[0]
  154.     section=[4] name=[(Intercept)] type=[LINEAR]
  155.     inla_parse_linear...
  156.         section[(Intercept)]
  157.         dir=[fixed.effect00000001]
  158.         file for covariates=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2]
  159.         read n=[200] entries from file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2]
  160.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 0/100  (idx,y) = (0, 1)
  161.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 1/100  (idx,y) = (1, 1)
  162.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 2/100  (idx,y) = (2, 1)
  163.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 3/100  (idx,y) = (3, 1)
  164.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 4/100  (idx,y) = (4, 1)
  165.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 5/100  (idx,y) = (5, 1)
  166.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 6/100  (idx,y) = (6, 1)
  167.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 7/100  (idx,y) = (7, 1)
  168.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 8/100  (idx,y) = (8, 1)
  169.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file5850123401c2] 9/100  (idx,y) = (9, 1)
  170.         prior mean=[0]
  171.         prior precision=[0]
  172.         compute=[1]
  173.         output:
  174.             summary=[1]
  175.             return.marginals=[1]
  176.             return.marginals.predictor=[0]
  177.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  178.             ncdf=[0]  [ ]
  179.     section=[5] name=[z] type=[LINEAR]
  180.     inla_parse_linear...
  181.         section[z]
  182.         dir=[fixed.effect00000002]
  183.         file for covariates=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0]
  184.         read n=[200] entries from file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0]
  185.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 0/100  (idx,y) = (0, -0.466793)
  186.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 1/100  (idx,y) = (1, 0.169768)
  187.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 2/100  (idx,y) = (2, 0.453294)
  188.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 3/100  (idx,y) = (3, -0.850103)
  189.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 4/100  (idx,y) = (4, 0.27291)
  190.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 5/100  (idx,y) = (5, 2.04257)
  191.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 6/100  (idx,y) = (6, 0.200488)
  192.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 7/100  (idx,y) = (7, -1.545)
  193.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 8/100  (idx,y) = (8, -1.81745)
  194.         file=[/tmp/RtmpfSOSbn/file585054fa8b4a/data.files/file58506922bbd0] 9/100  (idx,y) = (9, -1.27583)
  195.         prior mean=[0]
  196.         prior precision=[0.001]
  197.         compute=[1]
  198.         output:
  199.             summary=[1]
  200.             return.marginals=[1]
  201.             return.marginals.predictor=[0]
  202.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  203.             ncdf=[0]  [ ]
  204.     parse section=[9] name=[INLA.pardiso] type=[PARDISO]
  205.     inla_parse_pardiso...
  206.         section[INLA.pardiso]
  207.         verbose[0]
  208.         debug[0]
  209.         parallel.reordering[1]
  210.         nrhs[-1]
  211.     parse section=[8] name=[INLA.lp.scale] type=[LP.SCALE]
  212.     inla_parse_lp_scale...
  213.         section[INLA.lp.scale]
  214.  
  215.     Index table: number of entries[3], total length[102]
  216.         tag                            start-index     length
  217.         Predictor                               0        100
  218.         (Intercept)                           100          1
  219.         z                                     101          1
  220.     List of hyperparameters:
  221.         theta[0] = [Log precision for the Gaussian observations]
  222.  
  223.     parse section=[6] name=[INLA.Parameters] type=[INLA]
  224.     inla_parse_INLA...
  225.         section[INLA.Parameters]
  226.             lincomb.derived.correlation.matrix = [No]
  227.         global_node.factor = 2.000
  228.         global_node.degree = 2147483647
  229.         reordering = -1
  230.         constr.marginal.diagonal = 1.49e-08
  231. Contents of ai_param 0x5cc51e7f3420
  232.     Optimiser: DEFAULT METHOD
  233.         Option for GSL-BFGS2: tol  = 0.1
  234.         Option for GSL-BFGS2: step_size = 1
  235.         Option for GSL-BFGS2: epsx = 0.001
  236.         Option for GSL-BFGS2: epsf = 0.002
  237.         Option for GSL-BFGS2: epsg = 0.005
  238.         Restart: 0
  239.         Optimise: try to be smart: Yes
  240.         Optimise: use directions: Yes
  241.         Mode restart: Yes
  242.         Mode fixed: No
  243.         Mode use_mode: No
  244.         parallel linesearch [0]
  245.     Gaussian approximation:
  246.         tolerance_func = 0.002
  247.         tolerance_step = 5e-06
  248.         optpar_fp = 0
  249.         optpar_nr_step_factor = -0.1
  250.     Gaussian data: Yes
  251.     Strategy:   Use a mean-skew corrected Gaussian by fitting a Skew-Normal
  252.     Fast mode:  On
  253.     Use linear approximation to log(|Q +c|)? Yes
  254.         Method:  Compute the derivative exact
  255.     Parameters for improved approximations
  256.         Number of points evaluate:   9
  257.         Step length to compute derivatives numerically:  0.0001
  258.         Stencil to compute derivatives numerically:  5
  259.         Cutoff value to construct local neigborhood:     0.0001
  260.     Log calculations:    On
  261.     Log calculated marginal for the hyperparameters:     On
  262.     Integration strategy:    Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
  263.         f0 (CCD only):   1.100
  264.         dz (GRID only):  0.750
  265.         Adjust weights (GRID only):  On
  266.         Difference in log-density limit (GRID only):     6.000
  267.         Skip configurations with (presumed) small density (GRID only):   On
  268.     Gradient is computed using Central difference with step-length 0.005000
  269.     Hessian is computed using Central difference with step-length 0.070711
  270.     Hessian matrix is forced to be a diagonal matrix? [No]
  271.     Compute effective number of parameters? [Yes]
  272.     Perform a Monte Carlo error-test? [No]
  273.     Interpolator [Auto]
  274.     CPO required diff in log-density [3]
  275.     Stupid search mode:
  276.         Status     [On]
  277.         Max iter   [1000]
  278.         Factor     [1.05]
  279.     Numerical integration of hyperparameters:
  280.         Maximum number of function evaluations [100000]
  281.         Relative error ....................... [1e-05]
  282.         Absolute error ....................... [1e-06]
  283.     To stabilise the numerical optimisation:
  284.         Minimum value of the -Hessian [-inf]
  285.         Strategy for the linear term [Keep]
  286.     CPO manual calculation[No]
  287.     VB correction is [Enabled]
  288.         strategy                    = [mean]
  289.         verbose                     = [Yes]
  290.         f_enable_limit_mean         = [30]
  291.         f_enable_limit_var          = [25]
  292.         f_enable_limit_mean_max     = [1024]
  293.         f_enable_limit_variance_max = [768]
  294.         iter_max                    = [25]
  295.         emergency                   = [25.00]
  296.         hessian_update              = [2]
  297.         hessian_strategy            = [full]
  298.     Misc options:
  299.         Hessian correct skewness only [1]
  300. inla_build: check for unused entries in[/tmp/RtmpfSOSbn/file585054fa8b4a/Model.ini]
  301. inla_INLA_preopt_experimental...
  302.     Mode....................... [Compact]
  303.     Setup...................... [0.01s]
  304.     Sparse-matrix library...... [pardiso]
  305.     OpenMP strategy............ [pardiso]
  306.     num.threads................ [16:1]
  307.     blas.num.threads........... [1]
  308.     Density-strategy........... [High]
  309.     Size of graph.............. [2]
  310.     Number of constraints...... [0]
  311.     Optimizing sort2_id........ [304]
  312.     Optimizing sort2_dd........ [376]
  313.     Optimizing Qx-strategy..... serial[0.306] parallel [0.694] choose[serial]
  314.     Optimizing pred-strategy... plain [0.667] data-rich[0.333] choose[data-rich]
  315.  
  316.     List of hyperparameters:
  317.         theta[0] = [Log precision for the Gaussian observations]
  318.  
  319.  
  320. Compute initial values...
  321.     Iter[0] RMS(err) = 1.000, update with step-size = 0.971
  322.     Iter[1] RMS(err) = 0.102, update with step-size = 1.054
  323.     Iter[2] RMS(err) = 1.000, update with step-size = 0.026
  324.     Initial values computed in 0.0007 seconds
  325.         x[0] = 0.8211
  326.         x[1] = 0.8242
  327.         x[0] = 0.8211
  328.         x[1] = 0.8242
  329.  
  330. Optimise using DEFAULT METHOD
  331. Smart optimise part I: estimate gradient using forward differences
  332. malloc(): invalid size (unsorted)
  333. munmap_chunk(): invalid pointer
  334.  
  335.  *** inla.core.safe:  The inla program failed, but will rerun in case better initial values may help. try=1/1
  336.     Read ntt 16 1 with max.threads 16
  337.     Found num.threads = 16:1 max_threads = 16
  338.  
  339.     39a87469400fa169507c508366eca6ae7588cfdf - Wed Jun 19 21:58:47 2024 +0900
  340. Report bugs to <help@r-inla.org>
  341. Set reordering to id=[0] and name=[default]
  342. Process file[/tmp/RtmpfSOSbn/file58505f4ea2f0/Model.ini] threads[16] max.threads[16] blas_threads[1] nested[16:1]
  343. inla_build...
  344.     number of sections=[10]
  345.     parse section=[0] name=[INLA.libR] type=[LIBR]
  346.     inla_parse_libR...
  347.         section[INLA.libR]
  348.             R_HOME=[/usr/local/lib64/R]
  349.     parse section=[7] name=[INLA.Expert] type=[EXPERT]
  350.     inla_parse_expert...
  351.         section[INLA.Expert]
  352.             disable.gaussian.check=[0]
  353.             Measure dot.product.gain=[No]
  354.             cpo.manual=[0]
  355.             jp.file=[(null)]
  356.             jp.model=[(null)]
  357.     parse section=[1] name=[INLA.Model] type=[PROBLEM]
  358.     inla_parse_problem...
  359.         name=[INLA.Model]
  360.         R-INLA version = [24.06.19]
  361.         R-INLA build date = [19893]
  362.         Build tag = [devel]
  363.         System memory = [31.0Gb]
  364.         Cores = (Physical= 16, Logical= 16)
  365.         'char' is signed
  366.         BUFSIZ is 8192
  367.         openmp.strategy=[default]
  368.         pardiso-library installed and working? = [yes]
  369.         smtp = [pardiso]
  370.         strategy = [pardiso]
  371.         store results in directory=[/tmp/RtmpfSOSbn/file58505f4ea2f0/results.files]
  372.         output:
  373.             gcpo=[0]
  374.                 num.level.sets=[-1]
  375.                 size.max=[32]
  376.                 strategy=[Posterior]
  377.                 correct.hyperpar=[1]
  378.                 epsilon=[0.005]
  379.                 prior.diagonal=[0.0001]
  380.                 keep=[]
  381.                 remove.fixed=[1]
  382.                 remove=[]
  383.             cpo=[0]
  384.             po=[0]
  385.             dic=[0]
  386.             kld=[1]
  387.             mlik=[1]
  388.             q=[0]
  389.             graph=[0]
  390.             hyperparameters=[1]
  391.             config=[0]
  392.             config.lite=[0]
  393.             likelihood.info=[0]
  394.             internal.opt=[1]
  395.             save.memory=[0]
  396.             summary=[1]
  397.             return.marginals=[0]
  398.             return.marginals.predictor=[0]
  399.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  400.             ncdf=[0]  [ ]
  401.     parse section=[3] name=[Predictor] type=[PREDICTOR]
  402.     inla_parse_predictor ...
  403.         section=[Predictor]
  404.         dir=[predictor]
  405.         PRIOR->name=[loggamma]
  406.         hyperid=[53001|Predictor]
  407.         PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
  408.         PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
  409.         PRIOR->PARAMETERS=[1, 1e-05]
  410.         initialise log_precision[13.8155]
  411.         fixed=[1]
  412.         user.scale=[1]
  413.         n=[100]
  414.         m=[0]
  415.         ndata=[100]
  416.         compute=[0]
  417.         read offsets from file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc]
  418.         read n=[200] entries from file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc]
  419.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 0/100  (idx,y) = (0, 0)
  420.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 1/100  (idx,y) = (1, 0)
  421.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 2/100  (idx,y) = (2, 0)
  422.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 3/100  (idx,y) = (3, 0)
  423.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 4/100  (idx,y) = (4, 0)
  424.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 5/100  (idx,y) = (5, 0)
  425.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 6/100  (idx,y) = (6, 0)
  426.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 7/100  (idx,y) = (7, 0)
  427.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 8/100  (idx,y) = (8, 0)
  428.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file5850628aaedc] 9/100  (idx,y) = (9, 0)
  429.         A=[(null)]
  430.         Aext=[(null)]
  431.         AextPrecision=[1e+08]
  432.         output:
  433.             summary=[1]
  434.             return.marginals=[0]
  435.             return.marginals.predictor=[0]
  436.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  437.             ncdf=[0]  [ ]
  438.     parse section=[2] name=[INLA.Data1] type=[DATA]
  439.     inla_parse_data [section 1]...
  440.         tag=[INLA.Data1]
  441.         family=[GAUSSIAN]
  442.         likelihood=[GAUSSIAN]
  443.         file->name=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file585051266a64]
  444.         file->name=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file585031257209]
  445.         file->name=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506316efdb]
  446.         file->name=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58501f9a2b48]
  447.         read n=[300] entries from file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file585051266a64]
  448.             0/100  (idx,a,y,d) = (0, 1, 0.539796, 1)
  449.             1/100  (idx,a,y,d) = (1, 1, 1.06761, 1)
  450.             2/100  (idx,a,y,d) = (2, 1, 1.43897, 1)
  451.             3/100  (idx,a,y,d) = (3, 1, 0.151292, 1)
  452.             4/100  (idx,a,y,d) = (4, 1, 1.32971, 1)
  453.             5/100  (idx,a,y,d) = (5, 1, 2.9832, 1)
  454.             6/100  (idx,a,y,d) = (6, 1, 1.28958, 1)
  455.             7/100  (idx,a,y,d) = (7, 1, -0.552891, 1)
  456.             8/100  (idx,a,y,d) = (8, 1, -0.735916, 1)
  457.             9/100  (idx,a,y,d) = (9, 1, -0.0893465, 1)
  458.         likelihood.variant=[0]
  459.         initialise log_precision[4]
  460.         fixed0=[0]
  461.         PRIOR0->name=[loggamma]
  462.         hyperid=[65001|INLA.Data1]
  463.         PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
  464.         PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
  465.         PRIOR0->PARAMETERS0=[1, 5e-05]
  466.         initialise log_precision offset[72.0873]
  467.         fixed1=[1]
  468.         PRIOR1->name=[none]
  469.         hyperid=[65002|INLA.Data1]
  470.         PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
  471.         PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
  472.         PRIOR1->PARAMETERS1=[]
  473.         Link model   [IDENTITY]
  474.         Link order   [-1]
  475.         Link variant [-1]
  476.         Link a       [1]
  477.         Link ntheta  [0]
  478.         mix.use[0]
  479.     section=[4] name=[(Intercept)] type=[LINEAR]
  480.     inla_parse_linear...
  481.         section[(Intercept)]
  482.         dir=[fixed.effect00000001]
  483.         file for covariates=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411]
  484.         read n=[200] entries from file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411]
  485.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 0/100  (idx,y) = (0, 1)
  486.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 1/100  (idx,y) = (1, 1)
  487.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 2/100  (idx,y) = (2, 1)
  488.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 3/100  (idx,y) = (3, 1)
  489.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 4/100  (idx,y) = (4, 1)
  490.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 5/100  (idx,y) = (5, 1)
  491.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 6/100  (idx,y) = (6, 1)
  492.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 7/100  (idx,y) = (7, 1)
  493.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 8/100  (idx,y) = (8, 1)
  494.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506f7bf411] 9/100  (idx,y) = (9, 1)
  495.         prior mean=[0]
  496.         prior precision=[0]
  497.         compute=[1]
  498.         output:
  499.             summary=[1]
  500.             return.marginals=[0]
  501.             return.marginals.predictor=[0]
  502.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  503.             ncdf=[0]  [ ]
  504.     section=[5] name=[z] type=[LINEAR]
  505.     inla_parse_linear...
  506.         section[z]
  507.         dir=[fixed.effect00000002]
  508.         file for covariates=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162]
  509.         read n=[200] entries from file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162]
  510.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 0/100  (idx,y) = (0, -0.466793)
  511.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 1/100  (idx,y) = (1, 0.169768)
  512.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 2/100  (idx,y) = (2, 0.453294)
  513.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 3/100  (idx,y) = (3, -0.850103)
  514.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 4/100  (idx,y) = (4, 0.27291)
  515.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 5/100  (idx,y) = (5, 2.04257)
  516.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 6/100  (idx,y) = (6, 0.200488)
  517.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 7/100  (idx,y) = (7, -1.545)
  518.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 8/100  (idx,y) = (8, -1.81745)
  519.         file=[/tmp/RtmpfSOSbn/file58505f4ea2f0/data.files/file58506fee3162] 9/100  (idx,y) = (9, -1.27583)
  520.         prior mean=[0]
  521.         prior precision=[0.001]
  522.         compute=[1]
  523.         output:
  524.             summary=[1]
  525.             return.marginals=[0]
  526.             return.marginals.predictor=[0]
  527.             nquantiles=[3]  [ 0.025 0.5 0.975 ]
  528.             ncdf=[0]  [ ]
  529.     parse section=[9] name=[INLA.pardiso] type=[PARDISO]
  530.     inla_parse_pardiso...
  531.         section[INLA.pardiso]
  532.         verbose[0]
  533.         debug[0]
  534.         parallel.reordering[1]
  535.         nrhs[-1]
  536.     parse section=[8] name=[INLA.lp.scale] type=[LP.SCALE]
  537.     inla_parse_lp_scale...
  538.         section[INLA.lp.scale]
  539.  
  540.     Index table: number of entries[3], total length[102]
  541.         tag                            start-index     length
  542.         Predictor                               0        100
  543.         (Intercept)                           100          1
  544.         z                                     101          1
  545.     List of hyperparameters:
  546.         theta[0] = [Log precision for the Gaussian observations]
  547.  
  548.     parse section=[6] name=[INLA.Parameters] type=[INLA]
  549.     inla_parse_INLA...
  550.         section[INLA.Parameters]
  551.             lincomb.derived.correlation.matrix = [No]
  552.         global_node.factor = 2.000
  553.         global_node.degree = 2147483647
  554.         reordering = -1
  555.         constr.marginal.diagonal = 1.49e-08
  556. Contents of ai_param 0x580c382fb420
  557.     Optimiser: DEFAULT METHOD
  558.         Option for GSL-BFGS2: tol  = 0.1
  559.         Option for GSL-BFGS2: step_size = 1
  560.         Option for GSL-BFGS2: epsx = 0.002
  561.         Option for GSL-BFGS2: epsf = 0.004
  562.         Option for GSL-BFGS2: epsg = 0.01
  563.         Restart: 0
  564.         Optimise: try to be smart: No
  565.         Optimise: use directions: Yes
  566.         Mode restart: Yes
  567.         Mode fixed: No
  568.         Mode use_mode: No
  569.         parallel linesearch [0]
  570.     Gaussian approximation:
  571.         tolerance_func = 0.004
  572.         tolerance_step = 1e-05
  573.         optpar_fp = 0
  574.         optpar_nr_step_factor = -0.1
  575.     Gaussian data: Yes
  576.     Strategy:   Use the Gaussian approximation
  577.     Fast mode:  On
  578.     Use linear approximation to log(|Q +c|)? Yes
  579.         Method:  Compute the derivative exact
  580.     Parameters for improved approximations
  581.         Number of points evaluate:   9
  582.         Step length to compute derivatives numerically:  0.0001
  583.         Stencil to compute derivatives numerically:  5
  584.         Cutoff value to construct local neigborhood:     0.0001
  585.     Log calculations:    On
  586.     Log calculated marginal for the hyperparameters:     On
  587.     Integration strategy:    Use only the modal configuration (EMPIRICAL_BAYES)
  588.         f0 (CCD only):   1.100
  589.         dz (GRID only):  0.750
  590.         Adjust weights (GRID only):  On
  591.         Difference in log-density limit (GRID only):     6.000
  592.         Skip configurations with (presumed) small density (GRID only):   On
  593.     Gradient is computed using Central difference with step-length 0.005000
  594.     Hessian is computed using Central difference with step-length 0.070711
  595.     Hessian matrix is forced to be a diagonal matrix? [Yes]
  596.     Compute effective number of parameters? [Yes]
  597.     Perform a Monte Carlo error-test? [No]
  598.     Interpolator [Auto]
  599.     CPO required diff in log-density [3]
  600.     Stupid search mode:
  601.         Status     [On]
  602.         Max iter   [1000]
  603.         Factor     [1.05]
  604.     Numerical integration of hyperparameters:
  605.         Maximum number of function evaluations [100000]
  606.         Relative error ....................... [1e-05]
  607.         Absolute error ....................... [1e-06]
  608.     To stabilise the numerical optimisation:
  609.         Minimum value of the -Hessian [inf]
  610.         Strategy for the linear term [Keep]
  611.     CPO manual calculation[No]
  612.     VB-correction is [Disabled]
  613.     Misc options:
  614.         Hessian correct skewness only [1]
  615. inla_build: check for unused entries in[/tmp/RtmpfSOSbn/file58505f4ea2f0/Model.ini]
  616. inla_INLA_preopt_experimental...
  617.     Mode....................... [Compact]
  618.     Setup...................... [0.01s]
  619.     Sparse-matrix library...... [pardiso]
  620.     OpenMP strategy............ [pardiso]
  621.     num.threads................ [16:1]
  622.     blas.num.threads........... [1]
  623.     Density-strategy........... [High]
  624.     Size of graph.............. [2]
  625.     Number of constraints...... [0]
  626.     Optimizing sort2_id........ [310]
  627.     Optimizing sort2_dd........ [381]
  628.     Optimizing Qx-strategy..... serial[0.304] parallel [0.696] choose[serial]
  629.     Optimizing pred-strategy... plain [0.696] data-rich[0.304] choose[data-rich]
  630.  
  631.     List of hyperparameters:
  632.         theta[0] = [Log precision for the Gaussian observations]
  633.  
  634.  
  635. Compute initial values...
  636.     Iter[0] RMS(err) = 1.000, update with step-size = 0.971
  637.     Iter[1] RMS(err) = 0.102, update with step-size = 1.054
  638.     Iter[2] RMS(err) = 1.000, update with step-size = 0.026
  639.     Initial values computed in 0.0006 seconds
  640.         x[0] = 0.8211
  641.         x[1] = 0.8242
  642.         x[0] = 0.8211
  643.         x[1] = 0.8242
  644.  
  645. Optimise using DEFAULT METHOD
  646. malloc(): invalid size (unsorted)
  647. munmap_chunk(): invalid pointer
  648. Error in inla.core.safe(formula = formula, family = family, contrasts = contrasts,  :
  649.   The inla-program exited with an error. Unless you interupted it yourself, please rerun with verbose=TRUE and check the output carefully.
  650.   If this does not help, please contact the developers at <help@r-inla.org>.
  651. The inla program failed and the maximum number of tries has been reached.
  652. >
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