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Many resources for forensic scholars and practitioners, such as journal articles, guidance documents, and textbooks, address how to make a value of evidence assessment in the form of a likelihood ratio (LR) when deciding between two…

Applications · Statistics 2022-05-11 Steven Lund , Hari Iyer

The forensic science community has increasingly sought quantitative methods for conveying the weight of evidence. Experts from many forensic laboratories summarize their findings in terms of a likelihood ratio. Several proponents of this…

Applications · Statistics 2017-04-28 Steven P. Lund , Hari K. Iyer

In this article we provide a rebuttal against the possible perception that a single number, such as the Likelihood Ratio, can provide an objective, authoritative or definitive weight of evidence. We also illustrate the extent to which…

Applications · Statistics 2016-09-21 Steven P. Lund , Hari Iyer

For several decades, legal and scientific scholars have argued that conclusions from forensic examinations should be supported by statistical data and reported within a probabilistic framework. Multiple models have been proposed to quantify…

Applications · Statistics 2019-10-14 Cedric Neumann , Madeline A. Ausdemore

Bayesian inference as applied in a legal setting is about belief transfer and involves a plurality of agents and communication protocols. A forensic expert (FE) may communicate to a trier of fact (TOF) first its value of a certain…

Artificial Intelligence · Computer Science 2019-08-19 Jan A. Bergstra

Forensic examiners and attorneys need to know how to express evidence in favor or against a prosecutor's hypothesis in a way that avoids the prosecutor's fallacy and follows the modern reporting standards for forensic evidence. This article…

Applications · Statistics 2025-02-06 Maria Cuellar

Experts' beliefs embody a present state of knowledge. It is desirable to take this knowledge into account when doing analyses or making decisions. Yet ranking experts based on the merit of their beliefs is a difficult task. In this paper we…

Methodology · Statistics 2018-08-10 Duco Veen , Diederick Stoel , Naomi Schalken , Rens van de Schoot

Weighted Updating generalizes Bayesian updating, allowing for biased beliefs by weighting the likelihood function and prior distribution with positive real exponents. I provide a rigorous foundation for the model by showing that…

Probability · Mathematics 2016-02-09 Jesse Aaron Zinn

This article, produced as a result of the Symposium on Statistical Inference, is an introduction to the literature on the function of expertise, judgment, and choice in the practice of statistics and scientific research. In particular,…

Other Statistics · Statistics 2018-09-14 Naomi C Brownstein

In the Bayesian paradigm for presenting forensic evidence to court, it is recommended that the weight of the evidence be summarized as a likelihood ratio (LR) between two opposing hypotheses of how the evidence could have been produced.…

Applications · Statistics 2013-04-15 Niko Brümmer

The roles played by decision factors in making complex subject are decisions are characterized by how these factors affect the overall decision. Evidence that partially matches a factor is evaluated, and then effective computational rules…

Artificial Intelligence · Computer Science 2013-04-15 Gerald Shao-Hung Liu

When presenting forensic evidence, such as a DNA match, experts often use the Likelihood ratio (LR) to explain the impact of evidence . The LR measures the probative value of the evidence with respect to a single hypothesis such as 'DNA…

Applications · Statistics 2021-06-11 Norman Fenton , Martin Neil

Forensic scientists are often criticised for the lack of quantitative support for the conclusions of their examinations. While scholars advocate for the use of a Bayes factor to quantify the weight of forensic evidence, it is often…

Complex learning agents are increasingly deployed alongside existing experts, such as human operators or previously trained agents. However, it remains unclear how should learners optimally incorporate certain forms of expert data, which…

Machine Learning · Computer Science 2025-10-10 Daniel Jarne Ornia , Joel Dyer , Nicholas Bishop , Anisoara Calinescu , Michael Wooldridge

We consider the problem of performing Bayesian inference in probabilistic models where observations are accompanied by uncertainty, referred to as "uncertain evidence." We explore how to interpret uncertain evidence, and by extension the…

Machine Learning · Statistics 2023-01-27 Andreas Munk , Alexander Mead , Frank Wood

Evidence in probabilistic reasoning may be 'hard' or 'soft', that is, it may be of yes/no form, or it may involve a strength of belief, in the unit interval [0, 1]. Reasoning with soft, [0, 1]-valued evidence is important in many situations…

Artificial Intelligence · Computer Science 2019-07-02 Bart Jacobs

This paper presents some ideas and results of using uncertainty management methods in the presence of data in preference to other statistical and machine learning methods. A medical domain is used as a test-bed with data available from a…

Artificial Intelligence · Computer Science 2013-04-08 Mary McLeish , P. Yao , M. Cecile , T. Stirtzinger

The present letter to the editor is one in a series of publications discussing the formulation of hypotheses (propositions) for the evaluation of strength of forensic evidence. In particular, the discussion focusses on the issue of what…

Applications · Statistics 2017-04-26 Geoffrey Stewart Morrison , Ewald Enzinger , Cuiling Zhang

Lennard (2013) [Fingerprint identification: how far have we come? Aus J Forensic Sci. doi:10.1080/00450618.2012.752037] proposes that the numeric output of statistical models should not be presented in court (except "if necessary" / "if…

Methodology · Statistics 2020-12-23 Geoffrey Stewart Morrison , Reinoud D Stoel

Attempts to replicate probabilistic reasoning in expert systems have typically overlooked a critical ingredient of that process. Probabilistic analysis typically requires extensive judgments regarding interdependencies among hypotheses and…

Artificial Intelligence · Computer Science 2013-04-15 Marvin S. Cohen
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