prep_snv.md
In proximetricsR: Spectral Preprocessing and Chemometric Calibration of NIR Sensors

Standard normal variate returns correct values

Code
  process(X, prep_snv())
Output
              1001       1016       1031       1046       1061       1076
   [1,] -0.1248565 -0.2043233 -0.3032677 -0.3863736 -0.4473984 -0.5103451
   [2,] -0.2759478 -0.3328523 -0.4124245 -0.4770289 -0.5270084 -0.5763973
   [3,] -0.2386357 -0.3008495 -0.3878121 -0.4609483 -0.5191908 -0.5779478
   [4,] -0.1039285 -0.1679734 -0.2632671 -0.3459732 -0.4067272 -0.4706721
   [5,] -0.2165777 -0.2831262 -0.3707334 -0.4424774 -0.4984305 -0.5542669
   [6,] -0.5385152 -0.5641396 -0.6117631 -0.6533340 -0.6860169 -0.7188516
   [7,] -0.4048271 -0.4467805 -0.5084940 -0.5658045 -0.6103456 -0.6541938
   [8,] -0.3887002 -0.4459891 -0.5148130 -0.5748198 -0.6188008 -0.6584494
   [9,] -0.2206100 -0.2722474 -0.3464896 -0.4119316 -0.4616677 -0.5102608
  [10,] -0.5252585 -0.5493407 -0.5939696 -0.6333928 -0.6615029 -0.6869406
  [11,] -0.3530163 -0.4142000 -0.4885051 -0.5513251 -0.6005688 -0.6478707
              1091       1106       1121       1136       1151       1166
   [1,] -0.6018036 -0.6821988 -0.7159135 -0.6911278 -0.6198494 -0.5157775
   [2,] -0.6510318 -0.7172030 -0.7435847 -0.7114709 -0.6349101 -0.5330757
   [3,] -0.6620228 -0.7358651 -0.7643092 -0.7238852 -0.6363413 -0.5198352
   [4,] -0.5644518 -0.6494337 -0.6894843 -0.6591059 -0.5910999 -0.4936427
   [5,] -0.6376123 -0.7106253 -0.7408332 -0.7073727 -0.6308705 -0.5293889
   [6,] -0.7728796 -0.8173551 -0.8256022 -0.7775403 -0.6599898 -0.5345541
   [7,] -0.7240660 -0.7792209 -0.7921793 -0.7486567 -0.6209312 -0.5160206
   [8,] -0.7181579 -0.7713612 -0.7845914 -0.7517581 -0.6482973 -0.5567359
   [9,] -0.5895653 -0.6616999 -0.6891986 -0.6696108 -0.5637482 -0.4866142
  [10,] -0.7423217 -0.7876782 -0.7959254 -0.7522368 -0.6615343 -0.5467714
  [11,] -0.7175670 -0.7765006 -0.7914222 -0.7514431 -0.6454386 -0.5309068
              1181       1196       1211       1226       1241       1256
   [1,] -0.4138088 -0.3792009 -0.4395526 -0.6357385 -0.7873844 -0.8927786
   [2,] -0.4278147 -0.3990827 -0.4534989 -0.6399969 -0.7778563 -0.8706216
   [3,] -0.3854505 -0.3387755 -0.4022733 -0.6174528 -0.7786754 -0.8838435
   [4,] -0.3829093 -0.3627610 -0.4357350 -0.6528071 -0.8072006 -0.9213498
   [5,] -0.4189501 -0.3910927 -0.4511263 -0.6338653 -0.7743206 -0.8766647
   [6,] -0.4191308 -0.3615851 -0.4286989 -0.6060955 -0.7253208 -0.8000004
   [7,] -0.3996416 -0.3104577 -0.4087338 -0.6337013 -0.7784505 -0.8603288
   [8,] -0.4582190 -0.4075792 -0.4762052 -0.6499845 -0.7641365 -0.8323058
   [9,] -0.4112654 -0.3595713 -0.4513832 -0.6571573 -0.7964084 -0.8921658
  [10,] -0.4333511 -0.4154702 -0.4707328 -0.6246379 -0.7303041 -0.7980389
  [11,] -0.4144263 -0.3670169 -0.4329493 -0.6298736 -0.7673449 -0.8470550
              1271       1286       1301       1316       1331       1346
   [1,] -0.9812530 -1.0704729 -1.1547047 -1.2102047 -1.1753539 -1.0325544
   [2,] -0.9494870 -1.0227770 -1.0942960 -1.1406130 -1.0962277 -0.9539934
   [3,] -0.9672370 -1.0441907 -1.1230337 -1.1716261 -1.1348140 -0.9814757
   [4,] -1.0192181 -1.1120848 -1.2057480 -1.2710198 -1.2324860 -1.0849813
   [5,] -0.9622895 -1.0411981 -1.1274002 -1.1784401 -1.1392908 -0.9932925
   [6,] -0.8584857 -0.9085006 -0.9564775 -0.9848373 -0.9287961 -0.7952414
   [7,] -0.9259804 -0.9747492 -1.0320106 -1.0750710 -1.0248763 -0.8969782
   [8,] -0.8954801 -0.9504563 -1.0070625 -1.0464865 -0.9973822 -0.8645070
   [9,] -0.9763810 -1.0561592 -1.1385753 -1.2042410 -1.1656311 -1.0415843
  [10,] -0.8618355 -0.9154711 -0.9694392 -1.0008905 -0.9508864 -0.8140408
  [11,] -0.9195293 -0.9812433 -1.0406920 -1.0792459 -1.0293224 -0.8910515
              1361       1376         1391      1406      1421     1436     1451
   [1,] -0.7832279 -0.5538093 -0.148308241 0.3152549 0.9745204 1.508400 1.667334
   [2,] -0.7156955 -0.4669644 -0.056441194 0.4046211 0.9744216 1.444796 1.630842
   [3,] -0.7102922 -0.4466873 -0.049729730 0.3539862 0.9444719 1.442791 1.608115
   [4,] -0.8164735 -0.5368042 -0.092673736 0.3614093 0.9391463 1.434206 1.614703
   [5,] -0.7250610 -0.4637078 -0.064767775 0.3685024 0.9300034 1.431750 1.623234
   [6,] -0.5889950 -0.3794817  0.004845516 0.4927315 1.0392370 1.425379 1.587048
   [7,] -0.6737031 -0.4234802  0.009911713 0.4836588 0.9930043 1.343102 1.510977
   [8,] -0.6520476 -0.4191111  0.004191547 0.5048161 1.0398372 1.409066 1.580685
   [9,] -0.8281684 -0.5868028 -0.122181163 0.4072868 0.9573893 1.348385 1.536707
  [10,] -0.6070283 -0.3775698  0.016096593 0.4811262 0.9738608 1.336066 1.522309
  [11,] -0.6723691 -0.4308352 -0.016913923 0.4724580 1.0303318 1.414930 1.586727
            1466     1481     1496     1511     1526     1541     1556     1571
   [1,] 1.688857 1.664394 1.630560 1.531930 1.398006 1.311458 1.252524 1.272552
   [2,] 1.693747 1.686121 1.659602 1.567366 1.437445 1.347128 1.274109 1.285528
   [3,] 1.648163 1.649931 1.661064 1.583335 1.450635 1.354135 1.282031 1.304047
   [4,] 1.660797 1.663447 1.662706 1.573348 1.426453 1.315586 1.231065 1.246476
   [5,] 1.669996 1.672527 1.674674 1.582733 1.444152 1.347197 1.273086 1.285973
   [6,] 1.659854 1.664015 1.642186 1.577382 1.471059 1.377278 1.314765 1.330859
   [7,] 1.605417 1.645278 1.673487 1.637944 1.534638 1.409652 1.308437 1.323602
   [8,] 1.664053 1.683124 1.662572 1.588256 1.471407 1.367134 1.293789 1.302639
   [9,] 1.632840 1.661003 1.659448 1.596166 1.475593 1.365058 1.289064 1.319989
  [10,] 1.632930 1.671849 1.662936 1.599058 1.497730 1.412378 1.355306 1.377203
  [11,] 1.662081 1.673194 1.647656 1.574222 1.458190 1.361819 1.295626 1.312448
            1586
   [1,] 1.245800
   [2,] 1.252576
   [3,] 1.280496
   [4,] 1.210670
   [5,] 1.259955
   [6,] 1.315549
   [7,] 1.310574
   [8,] 1.281869
   [9,] 1.322391
  [10,] 1.367722
  [11,] 1.298951
  attr(,"preprocess_recipe")
  Spectral preprocessing recipe (device: "unspecified"): 
   - Step 1: prep_snv
  attr(,"processed_wavs")
  Spectral variables by preprocessing step:
    step_0: 40 spectral variables
    step_1: 40 spectral variables