|
[1]
|
A robust functional partial least squares for scalar‐on‐multiple‐function regression
Journal of Chemometrics,
2022
DOI:10.1002/cem.3394
|
|
|
|
|
[2]
|
On partial least‐squares estimation in scalar‐on‐function regression models
Journal of Chemometrics,
2022
DOI:10.1002/cem.3452
|
|
|
|
|
[3]
|
On partial least‐squares estimation in scalar‐on‐function regression models
Journal of Chemometrics,
2022
DOI:10.1002/cem.3452
|
|
|
|
|
[4]
|
On partial least‐squares estimation in scalar‐on‐function regression models
Journal of Chemometrics,
2022
DOI:10.1002/cem.3452
|
|
|
|
|
[5]
|
Functional approach and agro‐climatic information to improve the estimation of olive oil fatty acid content from near‐infrared data
Food Science & Nutrition,
2020
DOI:10.1002/fsn3.1312
|
|
|
|
|
[6]
|
Functional data clustering via hypothesis testing k-means
Computational Statistics,
2018
DOI:10.1007/s00180-018-0808-9
|
|
|
|
|
[7]
|
Functional data analysis, a new approach to aligning three-way liquid chromatographic with fluorescence detection data
Microchemical Journal,
2018
DOI:10.1016/j.microc.2018.06.041
|
|
|
|
|
[8]
|
Leaf water content estimation by functional linear regression of field spectroscopy data
Biosystems Engineering,
2018
DOI:10.1016/j.biosystemseng.2017.08.017
|
|
|
|
|
[9]
|
Gaussian process regression with functional covariates and multivariate response
Chemometrics and Intelligent Laboratory Systems,
2017
DOI:10.1016/j.chemolab.2017.02.001
|
|
|
|
|
[10]
|
Leaf water content estimation by functional linear regression of field spectroscopy data
Biosystems Engineering,
2017
DOI:10.1016/j.biosystemseng.2017.08.017
|
|
|
|
|
[11]
|
Assessment of table olive fermentation by functional data analysis
International Journal of Food Microbiology,
2016
DOI:10.1016/j.ijfoodmicro.2016.08.031
|
|
|
|
|
[12]
|
Review and application of functional data analysis to chemical data—The example of the comparison, classification, and database search of forensic ink chromatograms
Chemometrics and Intelligent Laboratory Systems,
2015
DOI:10.1016/j.chemolab.2015.07.006
|
|
|
|