16 papers · ranked by Valyu relevance
Richard R. Stein, Debora S. Marks, Chris Sander, Shi-Jie Chen
Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical…
Akatsuki Kimura, Antonio Celani, Hiromichi Nagao, Timothy Stasevich + 1 more
'Kazuyuki Nakamura'] Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental…
Michel Broniatowski, Igal Sason
This paper states that most commonly used minimum divergence estimators are MLEs for suited generalized bootstrapped sampling schemes. Optimality in the sense of Bahadur for associated tests of fit under such sampling is considered.
Antonio Calcagnì, Livio Finos, Gianmarco Altoé, Massimiliano Pastore
In this article, we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy (ME) approach. Unlike standard procedures that require equating the score function of the maximum likelihood problem at zero, we propose an alternative strategy where the score is instead…
Jarno Lintusaari, Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski + 1 more
'Jukka Corander'] Title: Abstract Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference…
Frank Kwasniok, Bryan C Daniels
A comprehensive methodology for semiparametric probability density estimation is introduced and explored. The probability density is modelled by sequences of mostly regular or steep exponential families generated by flexible sets of basis functions, possibly including boundary terms. Parameters are estimated by global…
Arwa M. Alshangiti, M. Kayid, B. Alarfaj
The purpose of this paper is to provide further study of the Marshall-Olkin log-logistic model that was first described by Gui (Appl Math Sci 7:3947-3961, [8]). This model is both useful and practical in areas such as reliability and life testing. Some statistical and reliability properties of this model are presented…
Giacomo Aletti, Nancy Flournoy, Caterina May, Chiara Tommasi
This study focuses on the estimation of the Emax dose-response model, a widely utilized framework in clinical trials, experiments in pharmacology, agriculture, environmental science, and more. Existing challenges in obtaining maximum likelihood estimates (MLE) for model parameters are often ascribed to computational…
Mintodê Nicodème Atchadé, Melchior N’bouké, Aliou Moussa Djibril, Shabnam Shahzadi + 6 more
'Shabnam Shahzadi' 'Eslam Hussam' 'Ramy Aldallal' 'Huda M. Alshanbari' 'Ahmed M. Gemeay' 'Abdal-Aziz H. El-Bagoury' 'Anoop Kumar'] We introduced a brand-new member of the family that is going to be referred to as the New Power Topp-Leone Generated (NPTL-G). This new member is one of a kind. Given the major functions…
C. M. Revathi, Rajesh Moharana
This study proposes the Log-Linear Failure Rate (Log-LFR) distribution, a novel extension of the classical Linear Failure Rate model achieved through a logarithmic transformation. The suggested logarithmic generator is characterized by its survival-based construction, permitting a natural hazard interpretation and an…
Wanting Wang, Zubair Ahmad, Omid Kharazmi, Clement Boateng Ampadu + 3 more
'E. H. Hafez' 'Marwa M. Mohie El-Din' 'Feng Chen'] As is already known, statistical models are very important for modeling data in applied fields, particularly in engineering, medicine, and many other disciplines. In this paper, we propose a new family to introduce new distributions suitable for modeling reliability…
Ali A. Al-Shomrani, A. I. Shawky, Osama H. Arif, Muhammad Aslam
This paper focuses on the application of Markov Chain Monte Carlo (MCMC) technique for estimating the parameters of log-logistic (LL) distribution which is dependent on a complete sample. To find Bayesian estimates for the parameters of the LL model OpenBUGS-established software for Bayesian analysis based on MCMC…
Ehsan Fayyazishishavan, Serpil Kılıç Depren, Feng Chen
The two-parameter of exponentiated Gumbel distribution is an important lifetime distribution in survival analysis. This paper investigates the estimation of the parameters of this distribution by using lower records values. The maximum likelihood estimator (MLE) procedure of the parameters is considered, and the Fisher…
Alex Capaldi, Tiffany N. Kolba, Eugene Demidenko
We propose novel estimators for the parameters of an exponential distribution and a normal distribution when the only known information is a sample of sample maxima; i.e., the known information consists of a sample of m values, each of which is the maximum of a sample of n independent random variables drawn from the…
Erik van Nimwegen, Andrea Pagnani
To give an example, assume all the information we have regarding a variable X is that it can take on n possible states or values. If this is really all the available information, then nothing distinguishes the n possibilities from each other and the symmetry of this situation forces the machine to assign an equal…
Zahra Amini Farsani, Volker J. Schmid, Udo Von Toussaint
Background: For the kinetic models used in contrast-based medical imaging, the assignment of the arterial input function named AIF is essential for the estimation of the physiological parameters of the tissue via solving an optimization problem. Objective: In the current study, we estimate the AIF relayed on the…