Article

Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets

2021-09-23

Abstract excerpt

Environmental scientists often have to predict a complex phenomenon from a heterogeneous collection of datasets. This is particularly challenging if there are systematic differences between them, as is often the case. Accounting for these differences requires a larger number of parameters and thus increases the risk of overfitting. We investigate how Bayesian hierarchical models can help mitigate this problem by a...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: b3ce8095-ff9f-5442-aafa-cd8b08131357
DOI: 10.1101/2021.09.20.461084

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasetsDOI 10.1101/2021.09.20.461084Read

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression.Semantic proximity Read

High-throughput phenotyping using VIS/NIR spectroscopy in the classification of soybean genotypes for grain yield and industrial traits.Semantic proximity Read

Generalizability and transferability of machine learning models using hyperspectral reflectance data for maize traits.Semantic proximity Read

Bayesian networks and structural equation models reveal genetic causal relationships between productivity, defense, and climate-adaptability traits in interior lodgepole pine.Semantic proximity Read

Machine Learning-Powered Models for Near-Infrared Spectrometers: Prediction of Protein in Multiple Grain CerealsSemantic proximity Read

A leaf-level spectral library to support high-throughput plant phenotyping: predictive accuracy and model transfer.Semantic proximity Read

Individual variability in tree allometry determines light resource allocation in forest ecosystems: a hierarchical Bayesian approach.Semantic proximity Read

On the modelling of tropical tree growth: the importance of intra-specific trait variation, non-linear functions and phenotypic integration.Semantic proximity Read

Adaptability and stability evaluation of maize hybrids using Bayesian segmented regression models.Semantic proximity Read

Genotype × environment × management analysis to define allometric rules between leaves and stems in wheat.Semantic proximity Read

Uncertainty Quantification of Climate Impact on Tobacco Yield: A Grid-Based Multimodal AI Framework for Dynamic Risk Stratification and Adaptive ManagementSemantic proximity Read

Multi metric evaluation of leaf wetness models for large-area application of plant disease modelsSemantic proximity Read