R. S. Dalmolin
Environmental Engineering · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 23 citations into it
- Analytical Chemistry — 22 citations into it
- Artificial Intelligence — 17 citations into it
Whom R. S. Dalmolin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from R. S. Dalmolin's perspective
Ordered by how strongly the researchers R. S. Dalmolin trusts endorse each paper. Same corpus, a different order for every researcher.
- Comparing support vector machines to PLS for spectral regression applications
- Robust tests for equality of variances
- MALDIquant: a versatile R package for the analysis of mass spectrometry data (Bioinform.)
- Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy
- Validation requirements for diffuse reflectance soil characterization models with a case study of VNIR soil C prediction in Montana
- Statistical Learning Theory
- Bagging Predictors
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- Greedy function approximation: A gradient boosting machine.
- The Elements of Statistical Learning
Their papers
- Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions (2019) — 109 citations
- A systematic study on the application of scatter-corrective and spectral-derivative preprocessing for multivariate prediction of soil organic carbon by Vis-NIR spectra (2018) — 241 citations
- Two preprocessing techniques to reduce model covariables in soil property predictions by Vis-NIR spectroscopy (2017) — 73 citations