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Nonlinear mixed effects modeling is a powerful tool when analyzing data from several entities in an experiment. In this paper, we present NLMEModeling, a package for mixed effects modeling in Wolfram Mathematica. NLMEModeling supports mixed…

Computation · Statistics 2020-11-16 Jacob Leander , Joachim Almquist , Anna Johnning , Julia Larsson , Mats Jirstrand

B. Sturmfels and S. Sullivant associated to any graph a toric ideal, called the cut ideal. We consider monomial cut ideals and we show that their algebraic properties such as the minimal primary decomposition, the property of having a…

Commutative Algebra · Mathematics 2011-05-19 Anda Olteanu

ProMoAI is a novel tool that leverages Large Language Models (LLMs) to automatically generate process models from textual descriptions, incorporating advanced prompt engineering, error handling, and code generation techniques. Beyond…

Databases · Computer Science 2024-08-09 Humam Kourani , Alessandro Berti , Daniel Schuster , Wil M. P. van der Aalst

We use initially regular sequences that consist of linear sums to explore the depth of $R/I^2$, when $I$ is a monomial ideal in a polynomial ring $R$. We give conditions under which these linear sums form regular or initially regular…

Commutative Algebra · Mathematics 2022-08-30 Louiza Fouli , Tài Huy Hà , Susan Morey

We investigate the structure and properties of symmetric ideals generated by general forms in the polynomial ring under the natural action of the symmetric group. This work significantly broadens the framework established in our earlier…

Commutative Algebra · Mathematics 2025-06-19 Alexandra Seceleanu , Liana Şega

In this paper, we introduce techniques for producing normal square-free monomial ideals from old such ideals. These techniques are then used to investigate the normality of cover ideals under some graph operations. Square-free monomial…

We study the problem of generating monomials of a polynomial in the context of enumeration complexity. In this setting, the complexity measure is the delay between two solutions and the total time. We present two new algorithms for…

Computational Complexity · Computer Science 2011-02-01 Yann Strozecki

The paper proposes a Riemannian Manifold Hamiltonian Monte Carlo sampler to resolve the shortcomings of existing Monte Carlo algorithms when sampling from target densities that may be high dimensional and exhibit strong correlations. The…

Computation · Statistics 2019-12-18 Mark Girolami , Ben Calderhead , Siu A. Chin

In this paper we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior…

Computation · Statistics 2016-12-08 Anabel Forte , Gonzalo Garcia-Donato , Mark Steel

In this article, we provide three generators of propositional formulae for arbitrary languages, which uniformly sample three different formulae spaces. They take the same three parameters as input, namely, a desired depth, a set of atomics…

Logic in Computer Science · Computer Science 2021-10-19 Ariel J. Roffe , Joaquin S. Toranzo Calderon

We introduce a Markov Chain Monte Carlo simulation and data analysis package that extends the CMBEASY software. We have taken special care in implementing an adaptive step algorithm for the Markov Chain Monte Carlo in order to improve…

Astrophysics · Physics 2007-05-23 Michael Doran , Christian M. Mueller

Additive models offer accurate and interpretable predictions for tabular data, a critical tool for statistical modeling. Recent advances in Neural Additive Models (NAMs) allow these models to handle complex machine learning tasks, including…

Machine Learning · Computer Science 2025-03-12 Mike Van Ness , Madeleine Udell

Process mining represents an important field in BPM and data mining research. Recently, it has gained importance also for practitioners: more and more companies are creating business process intelligence solutions. The evaluation of process…

Software Engineering · Computer Science 2016-07-29 Andrea Burattin

In this paper we study simplicial complexes as higher dimensional graphs in order to produce algebraic statements about their facet ideals. We introduce a large class of square-free monomial ideals with Cohen-Macaulay quotients, and a…

Commutative Algebra · Mathematics 2007-05-23 Sara Faridi

This article explains the usage of R package CausalModels, which is publicly available on the Comprehensive R Archive Network. While packages are available for sufficiently estimating causal effects, there lacks a package that provides a…

Methodology · Statistics 2023-07-19 Joshua Wolff Anderson , Cyril Rakovski

We introduce and study vertex cover algebras of weighted simplicial complexes. These algebras are special classes of symbolic Rees algebras. We show that symbolic Rees algebras of monomial ideals are finitely generated and that such an…

Commutative Algebra · Mathematics 2007-05-23 Juergen Herzog , Takayuki Hibi , Ngo Viet Trung

In the last chapter of his book "The Algebraic Theory of Modular Systems " published in 1916, F. S. Macaulay developped specific techniques for dealing with " unmixed polynomial ideals " by introducing what he called " inverse systems ".…

Analysis of PDEs · Mathematics 2012-12-21 Jean-François Pommaret

We introduce a detection algorithm for SAGBI basis in polynomial rings, analogous to a Gr\"obner basis detection algorithm previously proposed by Gritzmann and Sturmfels. We also present two accompanying software packages named…

Commutative Algebra · Mathematics 2024-04-26 Viktoriia Borovik , Timothy Duff , Elima Shehu

In the first part of this paper we study scrollers and linearly joined varieties. A particular class of varieties, of important interest in classical Geometry are Cohen--Macaulay varieties of minimal degree. They appear naturally studying…

Commutative Algebra · Mathematics 2009-09-29 Marcel Morales

Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed…

Applications · Statistics 2014-09-30 Alexey Miroshnikov , Erin Conlon
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