Comparison of the single channel and multichannel (multivariate) concepts of selectivity in analytical chemistry
Само за регистроване кориснике
2015
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Different measures of selectivity are in use for single channel and multichannel linear analytical measurements, respectively. It is important to understand that these two measures express related but still distinctly different features of the respective measurements. These relationships are clarified by introducing new arguments. The most widely used selectivity measure of multichannel linear methods (which is based on the net analyte signal, NAS, concept) expresses the sensitivity to random errors of a determination where all bias from interferents is computationally eliminated using pure component spectra. The conventional selectivity measure of single channel linear measurements, on the other hand, helps to estimate the bias caused by an interferent in a biased measurement. In single channel methods expert knowledge about the samples is used to limit the possible range of interferent concentrations. The same kind of expert knowledge allows improved (lower mean squared error, MSE) a...nalyte determinations also in "classical" multichannel measurements if those are intractable due to perfect collinearity or to high noise inflation. To achieve this goal bias variance tradeoff is employed, hence there remains some bias in the results and therefore the concept of single channel selectivity can be extended in a natural way to multichannel measurements. This extended definition and the resulting selectivity measure can also be applied to the so-called inverse multivariate methods like partial least squares regression (PLSR), principal component regression (PCR) and ridge regression (RR). (C) 2015 Elsevier B.V. All rights reserved.
Кључне речи:
Selectivity / Error inflation / Interference / Multivariate / Bias variance tradeoffИзвор:
Talanta, 2015, 139, 40-49Издавач:
- Elsevier Science Bv, Amsterdam
Финансирање / пројекти:
- Синтеза аминохинолина и њихових деривата као антималарика и инхибитора ботулинум неуротоксина А (RS-MESTD-Basic Research (BR or ON)-172008)
- OTKA, Hungary [K104724]
DOI: 10.1016/j.talanta.2015.02.030
ISSN: 0039-9140
PubMed: 25882406
WoS: 000353857500007
Scopus: 2-s2.0-84925791448
Колекције
Институција/група
Hemijski fakultet / Faculty of ChemistryTY - JOUR AU - Dorko, Zsanett AU - Verbić, Tatjana AU - Horvai, George PY - 2015 UR - https://cherry.chem.bg.ac.rs/handle/123456789/1703 AB - Different measures of selectivity are in use for single channel and multichannel linear analytical measurements, respectively. It is important to understand that these two measures express related but still distinctly different features of the respective measurements. These relationships are clarified by introducing new arguments. The most widely used selectivity measure of multichannel linear methods (which is based on the net analyte signal, NAS, concept) expresses the sensitivity to random errors of a determination where all bias from interferents is computationally eliminated using pure component spectra. The conventional selectivity measure of single channel linear measurements, on the other hand, helps to estimate the bias caused by an interferent in a biased measurement. In single channel methods expert knowledge about the samples is used to limit the possible range of interferent concentrations. The same kind of expert knowledge allows improved (lower mean squared error, MSE) analyte determinations also in "classical" multichannel measurements if those are intractable due to perfect collinearity or to high noise inflation. To achieve this goal bias variance tradeoff is employed, hence there remains some bias in the results and therefore the concept of single channel selectivity can be extended in a natural way to multichannel measurements. This extended definition and the resulting selectivity measure can also be applied to the so-called inverse multivariate methods like partial least squares regression (PLSR), principal component regression (PCR) and ridge regression (RR). (C) 2015 Elsevier B.V. All rights reserved. PB - Elsevier Science Bv, Amsterdam T2 - Talanta T1 - Comparison of the single channel and multichannel (multivariate) concepts of selectivity in analytical chemistry VL - 139 SP - 40 EP - 49 DO - 10.1016/j.talanta.2015.02.030 ER -
@article{ author = "Dorko, Zsanett and Verbić, Tatjana and Horvai, George", year = "2015", abstract = "Different measures of selectivity are in use for single channel and multichannel linear analytical measurements, respectively. It is important to understand that these two measures express related but still distinctly different features of the respective measurements. These relationships are clarified by introducing new arguments. The most widely used selectivity measure of multichannel linear methods (which is based on the net analyte signal, NAS, concept) expresses the sensitivity to random errors of a determination where all bias from interferents is computationally eliminated using pure component spectra. The conventional selectivity measure of single channel linear measurements, on the other hand, helps to estimate the bias caused by an interferent in a biased measurement. In single channel methods expert knowledge about the samples is used to limit the possible range of interferent concentrations. The same kind of expert knowledge allows improved (lower mean squared error, MSE) analyte determinations also in "classical" multichannel measurements if those are intractable due to perfect collinearity or to high noise inflation. To achieve this goal bias variance tradeoff is employed, hence there remains some bias in the results and therefore the concept of single channel selectivity can be extended in a natural way to multichannel measurements. This extended definition and the resulting selectivity measure can also be applied to the so-called inverse multivariate methods like partial least squares regression (PLSR), principal component regression (PCR) and ridge regression (RR). (C) 2015 Elsevier B.V. All rights reserved.", publisher = "Elsevier Science Bv, Amsterdam", journal = "Talanta", title = "Comparison of the single channel and multichannel (multivariate) concepts of selectivity in analytical chemistry", volume = "139", pages = "40-49", doi = "10.1016/j.talanta.2015.02.030" }
Dorko, Z., Verbić, T.,& Horvai, G.. (2015). Comparison of the single channel and multichannel (multivariate) concepts of selectivity in analytical chemistry. in Talanta Elsevier Science Bv, Amsterdam., 139, 40-49. https://doi.org/10.1016/j.talanta.2015.02.030
Dorko Z, Verbić T, Horvai G. Comparison of the single channel and multichannel (multivariate) concepts of selectivity in analytical chemistry. in Talanta. 2015;139:40-49. doi:10.1016/j.talanta.2015.02.030 .
Dorko, Zsanett, Verbić, Tatjana, Horvai, George, "Comparison of the single channel and multichannel (multivariate) concepts of selectivity in analytical chemistry" in Talanta, 139 (2015):40-49, https://doi.org/10.1016/j.talanta.2015.02.030 . .