Results 21 to 30 of about 40,132 (204)
The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry
Agribusiness, EarlyView.ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer +2 more
wiley +1 more source
Bayes’ Theorem and Naive Bayes Classifier
, 2019 The goal of this article is to give a mathematically rigorous yet easily accessible introduction to Bayes’ theorem and the foundations of naive Bayes learning. Starting from fundamental elements of probability theory, this text outlines all steps leading
Berrar, Daniel, Daniel Berrar
core +1 more source
Teaching Bayes’ Theorem: Strength of Evidence as Predictive Accuracy [PDF]
, 2017 Although teaching Bayes’ theorem is popular, the standard approach—targeting posterior distributions of parameters—may be improved. We advocate teaching Bayes’ theorem in a ratio form where the posterior beliefs relative to the prior beliefs equals the ...
Richard D. Morey +3 more
core +1 more source
Advances in causal discovery methods for ecological time series
Biological Reviews, EarlyView.ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki +6 more
wiley +1 more source
Explaining the Bayes' theorem graphically [PDF]
, 2018 The Bayes’ theorem on conditional probabilities is normally presented to students in introductory courses/modules on Statistics and Probability. This because most STEM students will make use of conditional probabilities in their professional lives with ...
Pablo Ballesteros-Perez (4862347) +2 more
core +1 more source
, 2023 Tema ovog rada je Bayesova formula. Kroz rad prolazimo i uvjetnu vjerojatnost budući da je formula zasnovana na istoj. Navest ćemo primjene i proći kroz nekolicinu primjera pokazujući na koje sve načine Bayesova formula može biti upotrebljena ...
Peulić, Ana
core +1 more source
Predicting cervical cancer DNA methylation from genetic data using multivariate CMMP
Canadian Journal of Statistics, EarlyView.Abstract Epigenetic modifications link the environment to gene expression and play a crucial role in tumour development. DNA methylation, in particular, is gaining attention in cancer research, including cervical cancer, the focus of this study.
Hang Zhang +5 more
wiley +1 more source
Canadian Journal of Statistics, EarlyView.Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne +2 more
wiley +1 more source
Bayesian inverse ensemble forecasting for COVID‐19
Canadian Journal of Statistics, EarlyView.Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source