Comparison of Different Calibration Methods Suited for Calibration Problems with Many Variables
1992 ◽
Vol 46
(12)
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pp. 1780-1784
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Keyword(s):
This paper describes and compares different kinds of statistical methods proposed in the literature as suited for solving calibration problems with many variables. These are: principal component regression, partial least-squares, and ridge regression. The statistical techniques themselves do not provide robust results in the spirit of calibration equations which can last for long periods. A way of obtaining this property is by smoothing and differentiating the data. These techniques are considered, and it is shown how they fit into the treated description.
1998 ◽
Vol 361
(5)
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pp. 465-472
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2019 ◽
Vol 42
(19-20)
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pp. 648-653
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1995 ◽
Vol 351
(6)
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pp. 571-576
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1990 ◽
Vol 9
(1)
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pp. 45-63
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Keyword(s):
2010 ◽
Vol 75
(5)
◽
pp. 1535-1539
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1996 ◽
Vol 4
(1)
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pp. 225-242
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