Results 11 to 20 of about 505,151 (313)

Setting the Stage: Statistical Collaboration Videos for Training the Next Generation of Applied Statisticians

open access: yesJournal of Statistics and Data Science Education, 2021
Collaborative work is inherent to being a statistician or data scientist, yet opportunities for training and exposure to real-world scenarios are often only a small part of a student’s academic program.
Julia L. Sharp   +2 more
doaj   +1 more source

An analysis of hot‐started ADMM for linear MPC

open access: yesIET Control Theory & Applications, 2021
A convergence analysis of the alternating direction method of multipliers (ADMM) for linear model predictive control (MPC) problems with regularization terms is addressed here.
Mitsuru Toyoda, Mirai Tanaka
doaj   +1 more source

Inference on a Multi-Patch Epidemic Model with Partial Mobility, Residency, and Demography: Case of the 2020 COVID-19 Outbreak in Hermosillo, Mexico

open access: yesEntropy, 2023
Most studies modeling population mobility and the spread of infectious diseases, particularly those using meta-population multi-patch models, tend to focus on the theoretical properties and numerical simulation of such models.
Albert Orwa Akuno   +2 more
doaj   +1 more source

Bounds on inference [PDF]

open access: yes2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2013
Lower bounds for the average probability of error of estimating a hidden variable X given an observation of a correlated random variable Y, and Fano's inequality in particular, play a central role in information theory. In this paper, we present a lower bound for the average estimation error based on the marginal distribution of X and the principal ...
Medard, Muriel   +5 more
openaire   +5 more sources

Continuous Reproducibility in GNSS Signal Processing

open access: yesIEEE Access, 2018
This paper discusses the reproducibility of scientific experiments in which global navigation satellite system (GNSS) signals play a role. After analyzing the factors that impact the reproducibility of an experiment in the given context, this paper ...
Carles Fernandez-Prades   +3 more
doaj   +1 more source

Foundations of Inference [PDF]

open access: yesAxioms, 2012
We present a simple and clear foundation for finite inference that unites and significantly extends the approaches of Kolmogorov and Cox. Our approach is based on quantifying lattices of logical statements in a way that satisfies general lattice symmetries.
Kevin H. Knuth, John Skilling
openaire   +5 more sources

One versus two doses: What is the best use of vaccine in an influenza pandemic?

open access: yesEpidemics, 2015
Avian influenza A (H7N9), emerged in China in April 2013, sparking fears of a new, highly pathogenic, influenza pandemic. In addition, avian influenza A (H5N1) continues to circulate and remains a threat.
Laura Matrajt   +3 more
doaj   +1 more source

A discrete Ramos-Louzada distribution for asymmetric and over-dispersed data with leptokurtic-shaped: Properties and various estimation techniques with inference

open access: yesAIMS Mathematics, 2022
In this paper, a flexible probability mass function is proposed for modeling count data, especially, asymmetric, and over-dispersed observations. Some of its distributional properties are investigated.
Ahmed Sedky Eldeeb   +2 more
doaj   +1 more source

Variational Inference for Logical Inference

open access: yesarXiv: Computation and Language, 2017
Functional Distributional Semantics is a framework that aims to learn, from text, semantic representations which can be interpreted in terms of truth. Here we make two contributions to this framework. The first is to show how a type of logical inference can be performed by evaluating conditional probabilities.
Emerson, Guy, Copestake, Ann
openaire   +3 more sources

Detecting Confounding in Multivariate Linear Models via Spectral Analysis

open access: yesJournal of Causal Inference, 2018
We study a model where one target variable Y$Y$ is correlated with a vector X:=(X1,…,Xd)$\textbf{X}:=(X_1,\dots,X_d)$ of predictor variables being potential causes of Y$Y$.
Janzing Dominik, Schölkopf Bernhard
doaj   +1 more source

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