[
https://issues.apache.org/jira/browse/MATH-1663?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17751294#comment-17751294
]
Hasan Diwan commented on MATH-1663:
-----------------------------------
WeightedObservedPoints obs = new WeightedObservedPoints();
double[] independentValues = new double[SIZE];
Range<Integer> xRange = Range.closed(0, SIZE);
List<Integer> independentSrc = ContiguousSet.create(xRange,
DiscreteDomain.integers()).asList();
for (Integer i : independentSrc) { obs.add(i, y.get(i).asDouble()); }
GaussianCurveFitter fitter = GaussianCurveFitter.create();
// what are the elements of the array supposed to represent?
double[] parameters = parameters = fitter.fit(obs.toList());
/* y is equal to:
1.314
1.3125
1.312
1.3035
1.3021
1.2947
1.2957
1.288
1.287
1.2769
1.2757
1.2738
1.2685
1.2722
1.2735
1.2765
1.286
1.291
1.283
1.2858
1.2891
1.2886
1.3006
1.2997
1.2964
NA
1.2833
1.2903
1.2933
1.2934
1.3026
1.3015
1.3029
1.3104
1.3084
1.3146
1.3158
1.3162
1.3237
1.3067
1.3128
1.3162
1.3182
1.3104
1.3053
1.3032
1.2984
1.2993
1.3014
1.3101
NA
1.3139
1.3206
1.3193
1.3154
1.3168
1.321
1.3137
1.3061
1.3045
1.2974
1.2982
1.2898
1.2827
1.2826
1.2807
1.2731
1.2779
1.2974
1.2965
1.302
1.3076
1.3144
1.3116
1.2978
NA
1.3031
1.3011
1.2749
1.2839
1.2842
1.2809
1.2776
NA
1.2804
1.2809
1.2729
1.2766
1.2789
1.2772
1.2742
1.2719
NA
1.2777
1.2749
1.2558
1.2524
1.2658
1.2635
1.257
1.2606
1.2644
1.2669
1.265
1.2681
NA
NA
1.2676
1.2627
1.2699
1.2763
NA
1.2598
1.2633
1.274
1.2757
1.2724
1.2764
1.2768
1.2836
NA
1.2761
1.2862
1.294
1.2898
NA
1.2955
1.3074
1.3027
1.3176
1.3158
1.3146
1.3062
1.3135
1.3094
1.3068
1.2947
1.2956
1.2966
1.2933
1.2862
1.2887
1.2865
1.2793
1.2857
NA
1.3036
NA
1.306
1.3067
1.3059
1.3252
1.3318
1.3274
1.3222
1.3186
1.3141
1.3148
1.3107
1.301
1.3095
1.3101
1.323
1.3281
1.3278
1.3223
1.3263
1.3191
1.3073
1.3219
1.3203
1.3215
1.3192
1.3088
1.3032
1.3144
1.3035
1.3181
1.3072
1.301
1.3048
1.3048
1.31
1.3068
1.3086
1.3105
1.3049
1.3036
1.3003
1.3003
1.2983
1.2943
1.2947
1.2901
1.293
1.2924
1.303
1.3091
1.3032
1.3139
1.3093
1.3052
1.3014
1.3013
1.3036
1.2961
1.2921
1.2878
1.2803
1.2723
1.2718
1.2747
1.2674
1.2666
1.27
NA
1.2668
1.2631
1.2619
1.262
1.2621
1.2675
1.2706
1.2713
1.274
1.2684
1.2724
1.2693
1.2678
1.2601
1.2568
1.2547
1.2625
1.27
1.2703
1.2728
1.2721
1.2697
1.2674
1.2704
1.2644
1.2599
1.2568
NA
1.2506
1.2503
1.2463
1.2507
1.2549
1.2553
1.2523
1.2408
1.2438
1.2494
1.25
1.2475
1.2449
1.2498
1.2471
1.2387
1.2236
1.2148
1.222
1.2145
1.2132
1.2165
1.2149
1.2158
1.2138
1.2085
1.207
1.2067
1.2068
1.2112
1.2152
1.2138
1.2153
1.2142
1.225
1.2261
1.2232
1.2288
1.2248
1.2197
1.2166
NA
1.2086
1.219
1.2337
1.2299
1.2368
1.2355
1.2329
1.2357
1.2462
1.2423
1.2493
1.2478
1.2481
1.2489
1.2428
1.2475
1.2363
1.2343
1.2312
1.2305
1.2242
1.2313
1.239
1.2309
1.2322
1.2206
1.2215
1.2382
1.2683
NA
1.2737
1.2854
1.2853
1.2904
1.2983
1.2948
1.2886
1.281
1.2833
1.286
1.2905
1.2872
1.2939
1.295
1.2906
1.287
1.2872
1.2829
1.279
NA
1.2855
1.284
1.2879
1.2901
1.2965
1.2926
1.2918
1.2915
1.2829
1.2885
1.285
1.2881
NA
1.2939
1.2936
1.3002
1.3095
1.3165
1.3127
1.3157
1.3178
1.3176
1.3133
1.3349
1.333
1.3116
1.3078
1.3034
1.3036
1.2917
1.2955
NA
1.3007
1.309
1.314
1.3269
NA
1.3128
1.3091
1.3163
1.3127
1.311
1.3069
1.306
1.2983
1.3018
1.303
1.3076
1.3029
NA
1.3047
1.3136
1.3104
1.3071
1.3054
1.2996
1.3012
1.3106
1.3195
1.3006
1.3029
1.3
1.2935
1.2908
1.2919
1.2945
1.2978
1.3051
1.3039
NA
1.3017
1.2934
1.2877
1.2966
1.2923
1.3004
1.2921
1.2876
1.2778
1.2791
1.2827
1.2836
1.2939
1.301
1.31
1.2933
1.2887
1.2541
1.2406
1.2278
1.2017
1.176
1.1662
1.1743
1.1492
1.1784
1.1763
1.214
1.236
1.2392
1.2454
1.2394
1.238
1.2228
1.2298
1.2343
1.2394
1.2458
1.2485
1.2518
1.2617
1.2523
1.2433
1.2503
1.2467
1.2266
1.2332
1.2369
1.2335
1.2421
1.2438
1.2429
1.2602
1.2509
1.243
1.2449
1.2347
1.2349
1.2436
1.233
1.2299
1.2225
1.2194
1.2129
1.2211
1.2255
1.2257
1.2227
1.2178
NA
1.2337
1.2231
1.2325
1.232
1.2472
1.2531
1.26
1.2608
1.2703
1.2694
1.2736
1.2758
1.2635
1.2527
1.2543
1.2586
1.2526
1.243
1.2362
1.2447
1.2531
1.2432
1.2406
1.2337
1.2279
1.2369
1.2474
1.2469
NA
1.2482
1.2572
1.2593
1.2614
1.2654
1.2614
1.2546
1.2586
1.2621
1.255
1.2658
1.2736
1.2729
1.2759
1.2791
1.2887
1.295
1.2974
1.3035
1.3133
1.3053
1.3059
1.3141
1.3147
1.3043
1.3082
1.3077
1.3047
1.3082
1.3108
1.3105
1.3228
1.3191
1.319
1.3098
1.3078
1.3136
1.3186
1.3229
1.3341
1.3375
1.3416
1.3315
1.3263
1.323
NA
1.3039
1.3011
1.2846
1.2788
1.2876
1.2866
1.298
1.2955
1.295
1.2794
1.2726
1.275
1.2739
1.2706
1.2865
1.2847
1.2921
1.2901
1.2928
1.2972
1.2945
1.2914
1.2944
1.3003
NA
1.2968
1.3023
1.2917
1.2931
1.2998
1.2951
1.3143
1.309
1.3039
1.3021
1.3067
1.2997
1.289
1.2933
1.2904
1.305
1.3021
1.3116
1.3162
1.3137
1.3234
NA
1.3142
1.3176
1.3197
1.3247
1.3299
1.3225
1.3294
1.33
1.335
1.3378
NA
NA
1.3338
1.3392
1.3348
1.3496
1.3485
1.3353
1.3358
1.3392
1.3293
1.3197
1.3324
1.3434
1.3503
1.3609
1.3497
1.3354
1.3349
1.351
NA
NA
1.3447
1.3512
1.3605
1.3662
NA
1.3551
1.362
1.3593
1.3551
1.3583
1.3522
1.3637
1.3631
1.369
1.3599
NA
1.3627
NA
1.3721
1.3685
1.3668
1.3729
1.3688
1.3727
1.3723
1.3672
1.3644
1.3652
1.3665
1.3714
1.3738
1.3796
1.385
1.3822
1.3855
NA
1.391
1.3848
1.3956
1.4025
1.4077
1.4092
1.4106
1.4105
1.3947
1.3938
1.3962
1.3978
1.3999
1.3817
1.381
1.3884
1.3899
1.398
1.3925
1.3866
1.3892
1.3888
1.3938
1.3872
1.3856
1.3795
1.3723
1.3722
1.3794
1.3793
1.3729
1.3795
1.3825
1.3825
1.3907
1.3849
1.3757
1.3739
1.3734
1.3741
1.3742
1.379
1.3781
1.3826
1.3977
1.3955
1.3936
1.3851
1.3845
1.389
1.3908
1.3917
1.3956
1.3838
1.3913
1.3873
1.3913
1.388
1.4
1.4153
1.4149
1.4081
1.4033
1.4096
1.4127
1.4184
1.4169
1.4182
1.4158
1.4147
1.4123
1.4129
1.4172
1.4188
NA
1.4168
1.4177
1.4099
1.4175
1.4179
1.4146
1.4124
1.4165
1.4114
1.4116
1.4073
1.411
1.3916
1.3817
1.3915
1.3921
1.3977
1.3907
1.3899
1.3895
1.3845
1.3806
1.378
1.3795
NA
1.3792
1.3792
1.3767
1.3842
1.3886
1.3847
1.3854
1.3849
1.3785
1.369
1.3615
1.3695
1.375
1.3749
1.3829
1.3884
1.3884
1.3966
1.3913
1.3886
1.3905
1.3912
1.3929
1.3873
1.3852
1.384
1.3866
1.3833
1.3857
1.3849
1.3739
1.3749
1.3673
1.3625
1.3717
1.3716
1.3723
1.3712
1.3769
1.3758
1.3747
1.379
1.3825
1.3862
NA
1.3792
1.3761
1.3855
1.3847
1.3844
1.3848
1.3837
1.3785
1.3755
1.3656
1.3663
1.3669
1.3745
1.3681
1.3712
1.3537
1.3439
1.347
1.3572
1.3602
1.364
1.3569
1.3634
1.363
NA
1.3605
1.3645
1.3684
1.3756
1.3726
1.3807
1.3821
1.3812
1.3741
1.3773
1.3772
1.3739
1.3804
1.3686
1.3679
1.3612
1.3659
1.3494
1.3491
1.3563
1.3551
1.347
NA
1.3412
1.3444
1.3429
1.3488
1.3489
1.3474
1.3412
1.3388
1.3332
NA
1.3322
1.3291
1.3252
1.3308
1.3305
1.3234
1.3252
1.3236
1.3236
1.3188
1.3262
1.3233
1.3225
1.3214
1.3325
1.3269
1.3222
1.3253
1.3345
1.341
NA
1.3438
1.3432
1.3475
1.35
NA
1.3469
1.3544
1.3573
1.3539
1.3583
1.3567
1.3622
1.3698
1.3724
1.367
NA
1.3588
1.3625
1.3642
1.3562
1.3447
1.3495
1.3516
1.3385
1.3417
1.3439
1.3505
1.3565
1.3602
1.3543
1.3533
1.3552
1.354
1.3636
1.3601
1.3516
1.3539
1.3585
1.3624
1.3585
NA
1.3597
1.3555
1.336
1.3407
1.3419
1.3318
1.3365
1.3326
1.3214
1.3115
1.3101
1.316
1.3108
1.3063
1.3044
1.3065
1.3096
1.3159
1.3169
1.3201
1.3258
1.3212
1.3183
1.3193
1.3091
1.3125
1.3149
1.3152
1.3114
1.3116
1.3101
1.3082
1.306
1.3032
1.3033
1.3031
1.3072
1.3052
1.3066
1.3019
1.3009
1.3055
1.3042
1.2848
1.2698
1.2617
1.2547
1.2443
1.2565
1.2523
1.251
1.2487
1.2334
1.2344
1.2335
1.2313
1.2317
1.2198
1.2242
1.227
1.2468
1.2396
1.2504
1.2492
1.2571
1.2544
1.2539
1.2582
1.2613
NA
1.2624
1.2472
1.2557
1.2496
1.2544
1.2594
1.2557
1.2511
1.233
1.217
1.2011
1.2057
1.2341
1.2201
NA
1.2277
1.228
1.224
1.2273
1.2305
1.22
1.2151
1.2162
1.2048
NA
1.1932
1.1907
1.1994
1.2036
1.1907
1.1905
1.1919
1.1827
1.1857
1.1989
1.2022
1.1989
1.1968
1.2019
1.2042
1.2036
1.2027
1.2126
1.2183
1.2278
1.2218
1.2132
1.2141
1.2061
1.2098
1.2089
1.2245
1.223
1.2132
1.209
1.209
1.203
1.197
1.181
1.1752
1.1844
1.1802
1.1803
1.1778
1.1718
1.1651
1.1647
1.1541
1.1582
NA
1.1549
1.1473
1.1489
1.16
1.1701
1.1526
1.1564
1.1472
1.1419
1.1403
1.1405
1.133
1.1269
1.0921
1.0703
1.0753
1.0832
1.1048
1.1134
1.1272
1.1446
1.1275
1.1133
1.1116
NA
1.1168
1.1096
1.1344
1.1208
1.1427
1.1307
1.1232
1.1288
1.1292
1.1295
1.1469
1.1615
1.1574
1.1573
1.1515
1.146
1.1467
1.1183
1.1279
1.1463
1.1595
1.1396
1.1677
NA
1.1728
1.189
1.1889
1.1812
1.1902
1.1785
1.188
1.204
NA
1.2102
1.2041
1.1996
1.1962
1.2252
1.2292
1.2169
1.2202
1.2194
1.2235
1.2311
1.2285
1.2375
1.2408
1.2206
1.2168
1.218
1.2146
1.2072
1.2032
1.2054
NA
1.2032
1.2034
1.206
1.2077
NA
1.197
1.2063
1.1902
1.2064
1.2206
1.2155
1.2125
1.2182
1.2194
NA
1.2264
1.2369
1.2366
1.2374
1.237
1.2323
1.2374
1.237
1.2379
1.2373
1.2324
1.2308
1.226
1.2073
1.2009
1.2013
1.2093
1.2157
1.2061
1.2136
1.2157
1.2031
1.2018
1.2012
NA
1.2111
1.2064
1.2016
1.1948
1.2036
1.2093
1.2034
1.1942
1.1996
1.2048
1.1857
1.1837
1.1922
1.2043
1.216
1.2146
1.2032
1.2111
1.2141
1.2257
1.2195
1.2232
1.2322
1.2225
1.2278
1.2341
1.2313
1.2368
1.2369
1.2403
1.2498
1.2469
1.2456
1.2422
1.2358
1.2409
1.2471
1.2531
1.2417
1.2359
1.2419
1.2442
1.2448
1.2419
1.2457
1.2398
1.2486
1.2471
1.2582
1.2495
1.2475
1.2547
1.258
1.265
1.2633
1.2618
1.2614
1.2501
1.2464
1.2526
1.2494
1.2475
1.2424
1.2464
1.2425
1.2423
1.2368
1.2325
1.2342
NA
1.2403
1.2396
1.2536
1.2468
1.244
1.2418
1.2451
1.2547
1.2579
1.2489
1.2611
1.2696
1.2762
1.2815
NA
1.2732
1.2737
1.275
1.2701
1.2724
1.2752
1.2637
1.2617
1.2709
1.2695
NA
1.271
1.2721
1.2838
1.2837
1.2901
1.2993
1.3097
1.3113
1.3078
1.3054
1.2898
1.2849
1.2854
1.2828
1.2876
1.293
1.287
1.287
*/
// Many thanks
> GuassianCurveFitter interpolate
> --------------------------------
>
> Key: MATH-1663
> URL: https://issues.apache.org/jira/browse/MATH-1663
> Project: Commons Math
> Issue Type: Bug
> Components: core
> Affects Versions: 3.6.1
> Reporter: Hasan Diwan
> Priority: Minor
>
> If the mean of my data is 1.54 and its standard deviation is 0.24, how is the
> interpolation using the GaussianCurveFitter yielding 5.58, when all the
> x-values differ by 1?
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