23 papers · ranked by Valyu relevance
Robert E. Gaunt, H Sutcliffe
We obtain bounds to quantify the distributional approximation in the delta method for vector statistics (the sample mean of n independent random vectors) for normal and non-normal limits, measured using smooth test functions. For normal limits, we obtain bounds of the optimal order n −1/2 rate of convergence, but for a…
Nathan Kallus, James O. McInerney
Epistemic uncertainty quantification is a crucial part of drawing credible conclusions from predictive models, whether concerned about the prediction at a given point or any downstream evaluation that uses the model as input. When the predictive model is simple and its evaluation differentiable, this task is solved by…
Shinichi Nakagawa, Paul C. D. Johnson, Holger Schielzeth
The coefficient of determination R^2^ quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R^2^ for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R^2^ that we…
Nicole E. Pashley
This work derives a finite population delta method. The delta method creates more general inference results when coupled with central limit theorem results for the finite population. This opens up a range of new estimators for which we can find finite population asymptotic properties. We focus on the use of this method…
Geir Kjetil Nilsen, Antonella Z. Munthe-Kaas, Hans J. Skaug, Morten Brun
'Morten Brun'] The Delta method is a classical procedure for quantifying epistemic uncertainty in statistical models, but its direct application to deep neural networks is prevented by the large number of parameters P. We propose a low cost variant of the Delta method applicable to L 2-regularized deep neural networks…
Natchaya Ratasukharom, Sa-Aat Niwitpong, Suparat Niwitpong, Hugo Hidalgo
'Hugo Hidalgo'] Thailand is currently grappling with a severe problem of air pollution, especially from small particulate matter (PM), which poses considerable threats to public health. The speed of the wind is pivotal in spreading these harmful particles across the atmosphere. Given the inherently unpredictable wind…
Eric Beutner, Henryk Zähle
The functional delta-method provides a convenient tool for deriving the asymptotic distribution of a plug-in estimator of a statistical functional from the asymptotic distribution of the respective empirical process. Moreover, it provides a tool to derive bootstrap consistency for plug-in estimators from bootstrap…
Jinyoung Hong, Eun‐Jung Cho, Hyun‐Ki Kim, Woochang Lee + 2 more
1## INTRODUCTION Delta check, first proposed during the 1970s,[jcla23550-bib-0001] is a patient-based quality control tool. Delta is defined as the difference between current test results and prior test results. If a delta value exceeds the established limit, the test result is held for manual review by laboratory…
Boaz Mohar, Jonathan B. Grimm, Ronak Patel, Timothy A. Brown + 4 more
Cells regulate function by synthesizing and degrading proteins. This turnover ranges from minutes to weeks, as it varies across proteins, cellular compartments, cell types, and tissues. Current methods for tracking protein turnover lack the spatial and temporal resolution needed to investigate these processes…
Authors not listed
Delta-machine learning (Δ-ML) is a highly cost-effective approach to developing high-level potential energy surfaces (PES) from a large number of low-level configurations. In particular, the high flexibility of the analytical PES-2008 is exploited to efficiently sample points from the low-level data set and, using…
Peng Wang, Yu Zhang, Bei-Qi Wang, Jian-Long Li + 5 more
'Dongdong Pan' 'Xian-Bo Wu' 'Wing Kam Fung' 'Ji-Yuan Zhou'] Background Skewed X chromosome inactivation (XCI), which is a non-random process, is frequently observed in both healthy and affected females. Furthermore, skewed XCI has been reported to be related to many X-linked diseases. However, no statistical method is…
Harish Gunasekaran, Leila Azizi, Virginie van Wassenhove, Sophie K. Herbst
Rhythmic activity in the delta frequency range (0.5 – 3 Hz) is a prominent feature of brain dynamics. Here, we examined whether spontaneous delta oscillations, as found in invasive recordings in awake animals, can be observed in non-invasive recordings pewwrformed in humans with magnetoencephalography (MEG). In humans…
Carlos Velázquez, Manuel Villarreal, Arturo Bouzas
The current work aims to study how people make predictions, under a reinforcement learning framework, in an environment that fluctuates from trial to trial and is corrupted with Gaussian noise. We developed a computer-based experiment where subjects were required to predict the future location of a spaceship that…
Patcharee Maneerat, Sa-Aat Niwitpong, Graciela Raga
The daily average natural rainfall amounts in the five regions of Thailand can be estimated using the confidence intervals for the common mean of several delta-lognormal distributions based on the fiducial generalized confidence interval (FGCI), large sample (LS), method of variance estimates recovery (MOVER)…
Authors not listed
The accurate prediction of fuel mixture properties is essential for the development of alternative fuels, yet remains challenging under data-scarce conditions due to the combinatorial complexity of multi-component systems. In this study, we present a systematic evaluation of three machine learning (ML)…
Theerapong Kaewprasert, Sa-Aat Niwitpong, Suparat Niwitpong, Lei Wang
'Lei Wang'] Precipitation and flood forecasting are difficult due to rainfall variability. The mean of a delta-gamma distribution can be used to analyze rainfall data for predicting future rainfall, thereby reducing the risks of future disasters due to excessive or too little rainfall. In this study, we construct…
Subrata Jana, John Herbert
Methods for computing core-level ionization energies using self-consistent field (SCF) calculations are evaluated and benchmarked. These include a "full core hole" or "Delta-SCF" approach that fully accounts for orbital relaxation upon ionization, but also methods based on Slater's transition concept, in which the…
Christoph Jacob, Johannes Neugebauer
The past years since the publication of our review on subsystem density-functional theory (sDFT) [WIREs Comput. Mol. Sci. 2014, 4:325--362] have witnessed a rapid development and diversification of quantum mechanical fragmentation and embedding approaches related to sDFT and frozen-density embedding (FDE). In this…
Subrata Jana, John Herbert
Methods for computing core-level ionization energies using self-consistent field (SCF) calculations are evaluated and benchmarked. These include a "full core hole" or "Delta-SCF" approach that fully accounts for orbital relaxation upon ionization, but also methods based on Slater's transition concept, in which the…
Han Geurdes
In this paper we ask if there is an interesting twist in mathematics of the Feynman propagator of the present day [1] formalism for the Dirac equation. The case studied is with only a potential function V . If there is no special integration order per step for e.g. dx(0) = dx1dx2dx3 and dp(0) = dp1dp2dp3, then a delta…
Kazunori D Yamada
In the deep learning era, a gradient descent method is the most common method to optimize parameters of neural networks. Among various mathematical optimization methods, a gradient descent method is the most naive method. Although controlling a learning rate of the method is necessary for quick convergence, the…
A. Mark Payne, Haoyang Wu, Hao-Wei Pang, Colin A. Grambow + 4 more
To obtain accurate enthalpies of formation of a chemical species, Hf, one needs a procedure to quantitatively connect the results from quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state, often along with additional empirical corrections. Although QM methods…
Mary Pitman, David Hahn, Gary Tresadern, David Mobley
Drug discovery is accelerated with computational methods such as alchemical simulations to estimate ligand affinities. In particular, relative binding free energy (RBFE) simulations are beneficial for lead optimization. To use RBFE simulations to compare prospective ligands in silico, researchers first plan the…