Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Franco Allegrini"'
Publikováno v:
Talanta Open, Vol 7, Iss , Pp 100235- (2023)
A tutorial is presented on the operation and properties of the non-linear multivariate regression model kernel partial least-squares (KPLS). After the discussion of a simple non-linear univariate problem, solved by regressing a dependent variable on
Externí odkaz:
https://doaj.org/article/60c1e224ce774d26bc134615232d11c4
Publikováno v:
Analytica Chimica Acta. 1226:340248
Concepts from data science, machine learning, deep learning and artificial neural networks are spreading in many disciplines. The general idea is to exploit the power of statistical tools to interpret complex and, in many cases, non-linear data. Spec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e92e1026397c5a9a8a33227e13a88af
https://doi.org/10.1016/j.aca.2022.340248
https://doi.org/10.1016/j.aca.2022.340248
Publikováno v:
Analytical chemistry. 92(18)
The use of machine learning for multivariate spectroscopic data analysis in applications related to process monitoring has become very popular since non-linearities in the relationship between signal and predicted variables are commonly observed. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4adb76570e17dbab3c73ddcfe50a4448
https://pubmed.ncbi.nlm.nih.gov/32812757
https://pubmed.ncbi.nlm.nih.gov/32812757
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Rosario. Instituto de Quimica Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquimicas y Farmaceutic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d8ba860874792f0de9e5af8c130194f
https://doi.org/10.1016/b978-0-12-409547-2.14612-8
https://doi.org/10.1016/b978-0-12-409547-2.14612-8
Publikováno v:
Analytica Chimica Acta. 1011:20-27
A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80a089a3b4f119f87b2f2c893c65c2c7
https://doi.org/10.1016/j.aca.2018.02.002
https://doi.org/10.1016/j.aca.2018.02.002
Publikováno v:
Chemometrics and Intelligent Laboratory Systems. 170:51-57
A maximum likelihood model is described for performing second-order multivariate calibration with unfolded principal component regression with residual bilinearization (MLU-PCR/RBL). It differs from the conventional RBL models based on U-PCR or U-PLS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4ab8012c20830bad52d761b6d599379
https://doi.org/10.1016/j.chemolab.2017.09.016
https://doi.org/10.1016/j.chemolab.2017.09.016
Publikováno v:
Analytica Chimica Acta. 903:51-60
Most of the current expressions used to calculate figures of merit in multivariate calibration have been derived assuming independent and identically distributed (iid) measurement errors. However, it is well known that this condition is not always va
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::163b2190c4ab3ba01ca9e7ef00693c67
https://doi.org/10.1016/j.aca.2015.11.028
https://doi.org/10.1016/j.aca.2015.11.028
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Rosario. Instituto de Quimica Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquimicas y Farmaceutic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31ced855291ed83be2750488ed8c4acd
https://doi.org/10.1016/b978-0-12-409547-2.13966-6
https://doi.org/10.1016/b978-0-12-409547-2.13966-6
Publikováno v:
Analytica chimica acta. 1003
Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a78c4f1912c33a78ab5a2242997f5b7
https://pubmed.ncbi.nlm.nih.gov/29317024
https://pubmed.ncbi.nlm.nih.gov/29317024
With a growing number of analytical methodologies incorporating multivariate calibration models, the development of suitable estimators of their analytical figures of merit is playing an important role in modern analytical chemistry. The main goal of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1f50bc1f687c5857929a9a49a2db140
http://pubs.rsc.org/en/Content/ArticleLanding/2017/AY/C6AY02916G
http://pubs.rsc.org/en/Content/ArticleLanding/2017/AY/C6AY02916G