Methodological Evaluation of Smallholder Farms Systems in Tanzania Using Bayesian Hierarchical Models for Risk Reduction Assessment

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Autori principali: Mwakalunga, Kamya, Tuyembe, Chituwo
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2014
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author Mwakalunga, Kamya
Tuyembe, Chituwo
author_facet Mwakalunga, Kamya
Tuyembe, Chituwo
contents <p>This study addresses a current research gap in Computer Science concerning Methodological evaluation of smallholder farms systems in Tanzania: Bayesian hierarchical model for measuring risk reduction in Tanzania. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of smallholder farms systems in Tanzania: Bayesian hierarchical model for measuring risk reduction, Tanzania, Africa, Computer Science, systematic review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19102012
institution Zenodo
language eng
publishDate 2014
publisher Zenodo
record_format zenodo
spellingShingle Methodological Evaluation of Smallholder Farms Systems in Tanzania Using Bayesian Hierarchical Models for Risk Reduction Assessment
Mwakalunga, Kamya
Tuyembe, Chituwo
Sub-Saharan
Bayesian
Hierarchical
Methodology
Smallholder
Risk
Evaluation
<p>This study addresses a current research gap in Computer Science concerning Methodological evaluation of smallholder farms systems in Tanzania: Bayesian hierarchical model for measuring risk reduction in Tanzania. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of smallholder farms systems in Tanzania: Bayesian hierarchical model for measuring risk reduction, Tanzania, Africa, Computer Science, systematic review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p>
title Methodological Evaluation of Smallholder Farms Systems in Tanzania Using Bayesian Hierarchical Models for Risk Reduction Assessment
topic Sub-Saharan
Bayesian
Hierarchical
Methodology
Smallholder
Risk
Evaluation
url https://doi.org/10.5281/zenodo.19102012