His primary areas of investigation include Statistics, Analytical chemistry, Principal component analysis, Pattern recognition and Artificial intelligence. His work on Plot, Multivariate analysis and Heteroscedasticity as part of general Statistics research is frequently linked to Rank and Statistical analysis, thereby connecting diverse disciplines of science. His study in the fields of Infrared spectroscopy under the domain of Analytical chemistry overlaps with other disciplines such as Analisis factorial.
His work deals with themes such as Euclidean distance, Data mining, Data set and Resolution, which intersect with Principal component analysis. The concepts of his Pattern recognition study are interwoven with issues in Calibration, Outlier and Chemometrics. His Artificial intelligence study integrates concerns from other disciplines, such as Regression diagnostic, Segmented regression, Bilinear interpolation and Collinearity.
Olav M. Kvalheim focuses on Analytical chemistry, Statistics, Principal component analysis, Chemometrics and Chromatography. His Analytical chemistry course of study focuses on Asphaltene and Mineralogy. He interconnects Biological system and Feature selection in the investigation of issues within Statistics.
As part of one scientific family, he deals mainly with the area of Principal component analysis, narrowing it down to issues related to the Multivariate statistics, and often Multivariate analysis. As part of his studies on Chemometrics, he frequently links adjacent subjects like Calibration. His study in Infrared spectroscopy is interdisciplinary in nature, drawing from both Monomer, Maturity and Diffuse reflection.
His scientific interests lie mostly in Lipoprotein, Physical activity, Internal medicine, Endocrinology and Very low-density lipoprotein. In his research on the topic of Endocrinology, Surgery is strongly related with Fatty acid. His Very low-density lipoprotein research includes themes of Low-density lipoprotein and High-density lipoprotein.
His Multivariate statistics study necessitates a more in-depth grasp of Statistics. In general Statistics study, his work on Mean squared error and Model selection often relates to the realm of Interpretation, Multiple correlation and Model validation, thereby connecting several areas of interest. His study looks at the intersection of Linear regression and topics like Binomial regression with Artificial intelligence.
Olav M. Kvalheim mainly focuses on Randomized controlled trial, Peer review, Physical activity, Metabolomics and Antimicrobial. His Cluster randomised controlled trial study in the realm of Randomized controlled trial connects with subjects such as Quality of life, Health promotion and Physical education. His Peer review research is multidisciplinary, incorporating elements of Disease cluster and Physical therapy.
His Physical activity research includes elements of Metabolic health and Multivariate statistics. Olav M. Kvalheim focuses mostly in the field of Metabolomics, narrowing it down to topics relating to Mass spectrometry and, in certain cases, Sample, Replicate, Replication and Analyte. His Chromatography study incorporates themes from Pyrenochaeta, Principal component analysis, Alternaria and Pyrenochaeta sp..
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: