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Familiar statistical tests and estimates are obtained by the direct observation of cases of interest: a clinical trial of a new drug, for instance, will compare the drug's effects on a relevant set of patients and controls. Sometimes,…

Methodology · Statistics 2010-12-09 Bradley Efron

One way to understand the role history plays on evolutionary trajectories is by giving ancient life a second opportunity to evolve. Our ability to empirically perform such an experiment, however, is limited by current experimental designs.…

Populations and Evolution · Quantitative Biology 2012-09-25 Betul Kacar , Eric Gaucher

Reduction of information entropy along with ever-increasing complexity are among the key signatures of living matter. Understanding the onset of such behavior in early prebiotic world is essential for solving the problem of origins of life.…

Populations and Evolution · Quantitative Biology 2018-10-17 Alexei V. Tkachenko , Sergei Maslov

Independence-based (IB) assignments to Bayesian belief networks were originally proposed as abductive explanations. IB assignments assign fewer variables in abductive explanations than do schemes assigning values to all evidentially…

Artificial Intelligence · Computer Science 2013-02-28 Eugene Santos , Solomon Eyal Shimony

Approximate Bayesian Computation (ABC) is typically used when the likelihood is either unavailable or intractable but where data can be simulated under different parameter settings using a forward model. Despite the recent interest in ABC,…

Methodology · Statistics 2019-12-24 Rafael Izbicki , Ann B. Lee , Taylor Pospisil

We apply the theory of learning to physically renormalizable systems in an attempt to develop a theory of biological evolution, including the origin of life, as multilevel learning. We formulate seven fundamental principles of evolution…

Populations and Evolution · Quantitative Biology 2022-10-12 Vitaly Vanchurin , Yuri I. Wolf , Mikhail I. Katsnelson , Eugene V. Koonin

Full Bayesian posteriors are rarely analytically tractable, which is why real-world Bayesian inference heavily relies on approximate techniques. Approximations generally differ from the true posterior and require diagnostic tools to assess…

Machine Learning · Statistics 2022-03-08 Luca Rendsburg , Agustinus Kristiadi , Philipp Hennig , Ulrike von Luxburg

In many cohorts (such as the UK Biobank) on which Mendelian Randomization studies are routinely performed, data on participants' longevity is inadequate as the majority of participants are still living. To nevertheless estimate effects on…

Methodology · Statistics 2025-08-06 Zach Shahn , Rehana Rasul , C. Mary Schooling

Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains it is crucial to be able to quantify evidence for the absence of a treatment effect. Bayesian hypothesis…

Biological activities are often seen entrained onto the day-night and other celestial mechanical cycles (e.g., seasonal and lunar), but studies on the origin of life have largely not accounted for such periodic external environmental…

Chaotic Dynamics · Physics 2024-08-21 Fan Zhang

We introduce an interacting particle system which models the inherited sterility method. Individuals evolve on $\mathbb{Z}^d$ according to a contact process with parameter $\lambda>0$. With probability $p \in [0,1]$ an offspring is fertile…

Probability · Mathematics 2025-11-18 Sonia Velasco

We consider a birth-death process with the birth rates $i\lambda$ and death rates $i\mu +i(i-1)\theta$, where $i$ is the current state of the process. A positive competition rate $\theta$ is assumed to be small. In the supercritical case…

Probability · Mathematics 2015-06-19 Serik Sagitov , Altynay Shaimerdenova

Research on the birth and evolution of life are reviewed with reference to the maximum entropy production principle (MEPP). It has been shown that this principle is essential for consistent understanding of the birth and evolution of life.…

Biological Physics · Physics 2025-04-22 Yasuji Sawada , Yasukazu Daigaku , Kenji Toma

Bayesian inference typically relies on specifying a parametric model that approximates the data-generating process. However, misspecified models can yield poor convergence rates and unreliable posterior calibration. Bayesian empirical…

Methodology · Statistics 2025-10-27 Kenyon Ng , Weichang Yu , Howard D. Bondell

After it was proposed that life on Earth might descend from seeding by an earlier civilization, some authors noted that this alternative offers a testable aspect: the seeds could be supplied with a signature that might be found in extant…

Other Quantitative Biology · Quantitative Biology 2017-07-12 Maxim A. Makukov , Vladimir I. shCherbak

Which factors govern the evolution of mutation rates and emergence of species? Here, we address this question using a first principles model of life where population dynamics of asexual organisms is coupled to molecular properties and…

Populations and Evolution · Quantitative Biology 2009-11-13 Muyoung Heo , Louis Kang , Eugene I. Shakhnovich

A phenomenological model of self-organization explaining the emergence of a complexity with features that apparently satisfy the specific criteria usually required for recognizing the appearance of life in laboratory is presented. The…

Adaptation and Self-Organizing Systems · Physics 2007-08-31 Erzilia Lozneanu , Mircea Sanduloviciu

We consider the challenges that arise when fitting complex ecological models to 'large' data sets. In particular, we focus on random effect models which are commonly used to describe individual heterogeneity, often present in ecological…

Methodology · Statistics 2022-05-17 Ruth King , Blanca Sarzo , Víctor Elvira

Consider a branching process with a homogeneous reproduction law. Sampling a single cell uniformly from the population at a time $T > 0$ and looking along the sampled cell's ancestral lineage, we find that the reproduction law is…

Populations and Evolution · Quantitative Biology 2022-05-30 David Cheek , Samuel G. G. Johnston

Many statistical models can be simulated forwards but have intractable likelihoods. Approximate Bayesian Computation (ABC) methods are used to infer properties of these models from data. Traditionally these methods approximate the posterior…

Machine Learning · Statistics 2018-04-03 George Papamakarios , Iain Murray