PSUADE_IO (Note : inputs not true inputs if pdf ~=U)
6 1 120
1 1
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2 1
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3 1
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4 1
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5 1
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6 1
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7 1
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8 1
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9 1
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10 1
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11 1
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12 1
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13 1
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14 1
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15 1
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16 1
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19 1
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20 1
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21 1
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22 1
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23 1
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26 1
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27 1
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29 1
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30 1
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31 1
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32 1
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42 1
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86 1
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  2.3731958030000002e+00
  4.8762722409999997e+00
  4.0144816400000000e-01
  8.0836473700000000e-01
  2.1831688599999999e-01
  9.2200000000000004e-02
87 1
  1.6557979820000000e+01
  4.7854758500000001e+00
  1.2934219210000000e+01
  4.3925505300000001e-01
  9.8076507999999996e-01
  9.5272744000000006e-02
  5.9400000000000001e-02
88 1
  1.7477270000000001e+01
  4.4813316810000003e+00
  7.9516603970000004e+00
  4.2227810900000001e-01
  8.9976105799999995e-01
  1.7811950900000001e-01
  9.3799999999999994e-02
89 1
  7.2470882339999996e+00
  3.8272832050000001e+00
  1.3102789110000000e+01
  4.8875221600000002e-01
  8.1272288800000003e-01
  1.7634404600000000e-01
  8.2199999999999995e-02
90 1
  1.0563949459999999e+00
  2.1435434230000001e+00
  5.7544609329999998e+00
  4.0914490700000000e-01
  9.0962086700000000e-01
  1.6026903500000000e-01
  8.6999999999999994e-02
91 1
  8.2657819279999991e+00
  4.1509758980000004e+00
  4.2862634630000001e+00
  4.1358441899999998e-01
  6.9578716600000001e-01
  9.3083734000000001e-02
  5.6200000000000000e-02
92 1
  4.9285756559999996e+00
  2.1020236780000001e+00
  1.1266640100000000e+01
  3.5661439200000000e-01
  5.9030541100000000e-01
  1.1700847100000000e-01
  5.9400000000000001e-02
93 1
  1.6235078690000002e+01
  3.8399333019999999e+00
  1.5629370480000000e+01
  4.1115923599999998e-01
  6.2558419600000004e-01
  1.6233725900000001e-01
  6.6199999999999995e-02
94 1
  8.5382441960000008e+00
  4.2917471259999997e+00
  1.3652758750000000e+01
  3.8690896000000002e-01
  7.8914914199999997e-01
  1.8083975999999999e-01
  7.6600000000000001e-02
95 1
  1.7158630230000000e+01
  4.3975295350000003e+00
  1.3870780269999999e+01
  3.5582287899999998e-01
  6.0532277300000004e-01
  1.0344710300000000e-01
  5.2999999999999999e-02
96 1
  1.8067472819999999e+01
  4.7240232090000003e+00
  1.7610788800000002e+01
  4.8382534100000002e-01
  8.4176088400000004e-01
  2.0319509199999999e-01
  9.0999999999999998e-02
97 1
  1.9442002630000001e+01
  2.7316023330000001e+00
  7.3079921450000001e+00
  4.0332353900000001e-01
  5.6299247299999999e-01
  9.8217908000000007e-02
  5.9400000000000001e-02
98 1
  1.7583867810000001e+01
  2.2145639070000001e+00
  1.3174943400000000e+01
  3.9425055399999998e-01
  7.4674467800000000e-01
  8.8129440000000003e-02
  5.0599999999999999e-02
99 1
  5.8838713340000002e+00
  3.1113396860000000e+00
  9.4909727289999992e+00
  4.1197186699999999e-01
  8.2451673000000003e-01
  1.6815051600000000e-01
  8.1400000000000000e-02
100 1
  1.6841160030000001e+01
  3.9780013319999998e+00
  1.6841768790000000e+01
  3.8488085500000002e-01
  7.7289343099999996e-01
  2.2344651500000001e-01
  7.0999999999999994e-02
101 1
  5.3543931569999996e+00
  3.5736382910000000e+00
  6.9396358610000002e+00
  4.9974982499999998e-01
  8.9167267699999997e-01
  1.4848666099999999e-01
  9.4600000000000004e-02
102 1
  1.0030918540000000e+01
  3.6073325320000000e+00
  1.5882872430000001e+01
  3.6514317400000001e-01
  7.0262613100000004e-01
  5.0363092999999998e-02
  3.4599999999999999e-02
103 1
  1.5383171400000000e+01
  4.9670362289999996e+00
  9.2364948469999995e+00
  4.5389438100000001e-01
  5.5467632700000002e-01
  2.1470910600000001e-01
  7.7799999999999994e-02
104 1
  1.6397954639999998e+01
  3.5367216220000000e+00
  3.5851149290000000e+00
  3.6939312499999999e-01
  7.2335448199999997e-01
  7.2389959000000004e-02
  4.3799999999999999e-02
105 1
  1.4667944609999999e+01
  3.9439700420000001e+00
  1.1784948580000000e+01
  3.8911008899999999e-01
  5.9764647699999995e-01
  1.2978876000000000e-01
  6.3399999999999998e-02
106 1
  9.8686849649999999e+00
  3.2614623450000000e+00
  1.1627858430000000e+01
  4.2028767000000000e-01
  6.1907534399999997e-01
  2.0804824699999999e-01
  7.6999999999999999e-02
107 1
  6.0632328190000004e+00
  3.9161661900000002e+00
  1.9250139170000001e+01
  4.4367645200000000e-01
  7.6446627599999994e-01
  5.7206721000000002e-02
  3.5400000000000001e-02
108 1
  1.2787938690000001e+01
  4.8663627150000002e+00
  1.8981561849999999e+01
  4.1986492500000000e-01
  7.3759386599999999e-01
  1.2023657000000000e-01
  5.4199999999999998e-02
109 1
  1.2334272690000001e+01
  4.0185573520000002e+00
  7.4075788769999997e+00
  4.7570859700000001e-01
  9.4870494000000005e-01
  8.5749797000000003e-02
  5.7000000000000002e-02
110 1
  7.4257156479999997e+00
  2.6228730950000001e+00
  4.0453897999999997e+00
  3.7942550300000000e-01
  6.0416349700000005e-01
  2.0180021900000000e-01
  7.1400000000000005e-02
111 1
  9.5237357550000006e+00
  3.0295135430000002e+00
  2.0007980220000000e+01
  4.3759597000000000e-01
  7.5580690800000006e-01
  1.9311556799999999e-01
  7.2999999999999995e-02
112 1
  7.6548934140000000e+00
  4.6822459609999996e+00
  1.0366289080000000e+01
  4.4654520199999997e-01
  6.8013999599999997e-01
  2.0877479400000001e-01
  8.0199999999999994e-02
113 1
  8.1450917599999995e-01
  3.4935042390000000e+00
  7.9198470839999997e+00
  4.6312615000000001e-01
  5.4462893599999995e-01
  1.1472066400000000e-01
  6.0199999999999997e-02
114 1
  1.5949059950000001e+01
  2.5043246340000000e+00
  9.6262133060000004e+00
  3.5359582400000000e-01
  9.3955573000000003e-01
  1.4174766999999999e-01
  7.4999999999999997e-02
115 1
  1.3609105370000001e+00
  2.8992708450000002e+00
  1.2784083490000000e+01
  3.6470420399999998e-01
  6.3009016299999998e-01
  2.3376616400000000e-01
  6.6199999999999995e-02
116 1
  2.5832309090000001e+00
  3.8645816520000000e+00
  4.5778880510000004e+00
  3.5847739299999998e-01
  9.3130725199999997e-01
  6.4877062999999999e-02
  4.2200000000000001e-02
117 1
  2.2283890810000000e+00
  2.3465860919999999e+00
  9.7948267869999999e+00
  4.2297785999999998e-01
  6.6801500000000003e-01
  5.3280480999999998e-02
  3.6999999999999998e-02
118 1
  6.2249755779999996e+00
  2.6985887150000001e+00
  1.1944873230000001e+01
  4.7023423600000003e-01
  9.7679397000000001e-01
  2.1675301699999999e-01
  1.0500000000000000e-01
119 1
  3.4727652750000000e+00
  3.9934345100000002e+00
  6.6256760830000001e+00
  4.1724044900000001e-01
  5.2998000099999998e-01
  1.8763795100000000e-01
  7.8200000000000006e-02
120 1
  2.0000224679999999e+01
  3.6344394670000000e+00
  8.8627777329999997e+00
  4.3181116000000003e-01
  8.2661613099999998e-01
  2.2858656799999999e-01
  1.0140000000000000e-01
PSUADE_IO
PSUADE
INPUT
   dimension = 6
   variable 1 t1:P_0  =   4.8779439400000002e-01   2.0000224679999999e+01
   variable 2 t2:beta  =   2.0000728950000002e+00   5.0000000000000000e+00
   variable 3 t3:StatWeight  =   2.9636698739999998e+00   2.0007980220000000e+01
   variable 4 t4:ep_gstar  =   3.5015843499999999e-01   4.9974982499999998e-01
   variable 5 t5:VelfacCoeff  =   5.0113757199999998e-01   9.9986000399999997e-01
   variable 6 x1:InitConc  =   5.0363092999999998e-02   2.4981387599999999e-01
#  PDF <inpNum> N  <mean> <std>
#  PDF <inpNum> L  <logmean> <std>
#  PDF <inpNum> T  <center> <halfbasewidth>
#  PDF <inpNum> B  <alpha> <beta>
#  PDF <inpNum> G  <alpha> <beta>
#  PDF <inpNum> W  <lambda> <K>
#  PDF <inpNum> IG <alpha> <beta>
#  PDF <inpNum> C  <X0> <gamma>
#  PDF <inpNum> E  <lambda>
#  PDF <inpNum> F  <D1> <D2>
#  PDF <inpNum> S  <filename> <index>
#  COR <inpNum> <inpNum> <value>
#  num_fixed = <count>
#  fixed <num> = <value>
END
OUTPUT
   dimension = 1
   variable 1 y2:LocFilling 
END
METHOD
   sampling = MC
#  sampling = FACT
#  sampling = LH
#  sampling = OA
#  sampling = OALH
#  sampling = MOAT
#  sampling = SOBOL
#  sampling = LPTAU
#  sampling = METIS
#  sampling = FAST
#  sampling = BBD
#  sampling = PBD
#  sampling = FF4
#  sampling = FF5
#  sampling = CCI4
#  sampling = CCI5
#  sampling = CCIF
#  sampling = CCF4
#  sampling = CCF5
#  sampling = CCFF
#  sampling = CCC4
#  sampling = CCC5
#  sampling = CCCF
#  sampling = SFAST
#  sampling = UMETIS
#  sampling = GMOAT
#  sampling = GMETIS
#  sampling = SPARSEGRID
#  sampling = LSA
#  sampling = RFF4
#  sampling = RFF5
   num_samples = 120
   num_replications = 1
   num_refinements = 0
   refinement_size = 10000000
   reference_num_refinements = 0
#  refinement_type = adaptive
#  randomize
#  randomize_more
#  an example of settings: input 1 with 3 settings
#  input_settings 1 3
#                 0.0
#                 0.5
#                 1.0
#  random_seed = 2147483647
END
APPLICATION
   driver = NONE
   opt_driver = NONE
   aux_opt_driver = NONE
   ensemble_driver = NONE
   ensemble_opt_driver = NONE
#  max_parallel_jobs = 1
#  min_job_wait_time = 1
   max_job_wait_time = 1000000
#  nondeterministic
#  launch_only
#  limited_launch_only
#  gen_inputfile_only
#  ensemble_run_mode
#  launch_interval = 1
#  save_frequency = 1000000
END
ANALYSIS
##**********************************************
## Moment - basic statistics
#  analyzer method = Moment
##==============================================
## MainEffect - raw data main effect analysis
#  analyzer method = MainEffect
##==============================================
## TwoParamEffect - raw data pairwise analysis
#  analyzer method = TwoParamEffect
##==============================================
## ANOVA - analysis of variance
#  analyzer method = ANOVA
##==============================================
## GLSA - gradient-based sensitivity analysis
#  analyzer method = GLSA
##==============================================
## RSFA - response surface analysis
#  analyzer method = RSFA
##==============================================
## MOAT - Morris screening analysis
#  analyzer method = MOAT
##==============================================
## SOBOL - Sobol' analysis on Sobol' samples
#  analyzer method = Sobol
##==============================================
## Correlation - classical correlation analysis
#  analyzer method = Correlation
##==============================================
## Integration - find area under response surface
#  analyzer method = Integration
##==============================================
## FAST - total sensitivity analysis using FAST samples
#  analyzer method = FAST
##==============================================
## FF - screening using fractional factorial samples
#  analyzer method = FF
##==============================================
## PCA - principal component analysis
#  analyzer method = PCA
##==============================================
## RSMSobol1 - response surface based main effect
#  analyzer method = RSMSobol1
##==============================================
## RSMSobol2 - response surface based pairwise effect
#  analyzer method = RSMSobol2
##==============================================
## RSMSobolTSI - response surface based total effect
#  analyzer method = RSMSobolTSI
##==============================================
## RSMSobolG - response surface based group effect
#  analyzer method = RSMSobolG
##==============================================
## ARSM - adaptive NN-based response surface analysis
#  analyzer method = ARSMNN
##==============================================
## ARSM - adaptive MARS-based response surface analysis
#  analyzer method = ARSM
##==============================================
## REL - reliability analysis
#  analyzer method = REL
##==============================================
## DELTA - Delta test for parameter screening
#  analyzer method = DELTA
##==============================================
## LSA - local sensitivity analysis
#  analyzer method = LSA
##**********************************************
   analyzer output_id  = 1
##**********************************************
##RS: MARS - multivariate adaptive regression
   analyzer rstype = MARS
##==============================================
##RS: linear - linear regression
#  analyzer rstype = linear
##==============================================
##RS: quadratic - quadratic regression
#  analyzer rstype = quadratic
##==============================================
##RS: cubic - third-order polynomial
#  analyzer rstype = cubic
##==============================================
##RS: quartic - fourth-order polynomial
#  analyzer rstype = quartic
##==============================================
##RS: selective - selected polynomial order terms
#  analyzer rstype = selective_regression
##==============================================
##RS: GP1 - Gaussian process by MacKay
#  analyzer rstype = GP1
##RS: GP2 - Gaussian process by Tong
#  analyzer rstype = GP2
##==============================================
##RS: SVM - support vector machine
#  analyzer rstype = SVM
##==============================================
##RS: PWL - piecewise linear approximation
#  analyzer rstype = PWL
##==============================================
##RS: TGP - treed Gaussian process by Lee et al.
#  analyzer rstype = TGP
##==============================================
##RS: MARSBag - MARS with bagging
#  analyzer rstype = MARSBag
##==============================================
##RS: sum_of_trees based on repeated bisections
#  analyzer rstype = sum_of_trees
##==============================================
##RS: Legendre - Legendre polynomial regression
#  analyzer rstype = Legendre
##==============================================
##RS: user - user provides basis functions
#  analyzer rstype = user_regression
##==============================================
##RS: sparse_grid - only with special quadrature pts 
#  analyzer rstype = sparse_grid_regression
##==============================================
##RS: Krigining - using 2nd order correlation
#  analyzer rstype = Kriging
##==============================================
##RS: splines - splines on 2D/3D grid samples
#  analyzer rstype = splines
##==============================================
##RS: KNN - k-nearest neighbors
#  analyzer rstype = KNN
##==============================================
##RS: RBF - radial basis function
#  analyzer rstype = RBF
##==============================================
##RS: ACOSSO - Curt Storlie's ACOSSO
#  analyzer rstype = Acosso
##==============================================
##RS: BSSANOVA - Curt Storlie's BSSANOVA
#  analyzer rstype = Bssanova
##==============================================
##RS: psuade_regression - PSUADE's internal function
#  analyzer rstype = psuade_regression
##==============================================
##RS: RBFBag - RBF with bootstraps
#  analyzer rstype = RBFBag
##==============================================
##RS: PLS - partial least squares (correlated inputs)
#  analyzer rstype = PLS
##==============================================
##RS: MRBF - multiple RBF
#  analyzer rstype = MRBF
##==============================================
##RS: MGP3 - multiple GP3
#  analyzer rstype = MGP3
##==============================================
##RS: MMARS - multiple MARS
#  analyzer rstype = MMARS
##==============================================
##RS: MTGP - multiple TGP
#  analyzer rstype = MTGP
##==============================================
#  analyzer rs_legendre_order = -1
#  analyzer rs_mars_num_bases = -1
#  analyzer rs_mars_interaction = -1
#  analyzer rs_num_mars = -1
#  analyzer rs_kriging_mode = -1
#  analyzer rs_kriging_tol = -1
#  analyzer opt_save_history
#  analyzer opt_use_history
#  analyzer regression_wgt_id = -1
#  graphics
#  sample_graphics
   analyzer threshold = 1.000000e+00
   rs_max_pts = 10000
##==============================================
## rs_constraint - for constrained UA/SA analysis
#  analyzer rs_constraint = psData indexFile Lbnd Ubnd
##==============================================
## moat_constraint - for constrained MOAT analysis
## analyzer moat_constraint = psData indexFile Lbnd Ubnd
##==============================================
## rs_index_file - use rs but fix some inputs
#  analyzer rs_index_file = <indexFile>
##==============================================
## rs_index_sample_file - sample for some inputs
#  analyzer rs_index_sample_file = <sampleFile>
##==============================================
## crude - optimize in raw data or rs spaces
#  optimization method = crude
##==============================================
## minpack - optimize with user provided gradients
#  optimization method = minpack
##==============================================
## sm - space mapping optimization
#  optimization method = sm
##==============================================
## mm - manifold mapping optimization
#  optimization method = mm
##==============================================
## mm - adaptive manifold mapping optimization
#  optimization method = mm_adaptive
##==============================================
## cobyla: nonlinear inequality-constrained opt
#  optimization method = cobyla
##==============================================
## bobyqa: bound-constrained optimization
#  optimization method = bobyqa
##==============================================
## lincoa: linear inequality constrained opt
#  optimization method = lincoa
##==============================================
## newuoa: unconstrained optimization
#  optimization method = newuoa
##==============================================
## lbfgs - with derivatives
#  optimization method = lbfgs
##==============================================
##  sce: genetic algorithm-type optimization
#  optimization method = sce
##==============================================
## moo - multi-objective optimization
#  optimization method = moo
##==============================================
## ouu - optimization under uncertainty
#  optimization method = ouu
##==============================================
## ouu_unconstr - ouu with no constraints 
#  optimization method = ouu_unconstr
##==============================================
## ouu_ineq_constr - ouu with inequality constraints 
#  optimization method = ouu_ineq_constr
##==============================================
## ouu_lbfgs - ouu with derivatives
#  optimization method = ouu_lbfgs
##==============================================
## nomad - mixed integer 
#  optimization method = nomad
##==============================================
## ouu - mixed integer 
#  optimization method = ouu_minlp
#***********************************************
#  optimization num_local_minima = 0
#  optimization use_response_surface
#  optimization print_level = 0
#  optimization num_fmin = 0
#  optimization output_id = 0
#  optimization max_feval = 10000
#  optimization deltax = 1.0e-6
#  optimization fmin = not defined
#  optimization cutoff = not defined
#  optimization tolerance = not defined
#  printlevel 
#  file_write matlab
#  use_input_pdfs
#  constraint_op_and
END
END
