Bayesian robustness under a skew-normal class of prior distribution

We develop a global sensitivity analysis to measure the robustness of the Bayesian estimators with respect to a class of prior distributions. This class arises when we consider multiplicative contamination of a base prior distribution. A similar structure was presented by van der Linde [12]. Some particular specifications for this multiplicative contamination class coincide with well known families of skewed distributions. In this paper, we explore the skew-normal multiplicative contamination class for the prior distribution of the location parameter of a normal model. Results of a Bayesian conjugation and expressions for some measures of distance between posterior means and posterior variance are obtained. We also elaborate on the behavior of the posterior means and of the posterior variances through a simulation study.     

中学生学习自我效能感、学习策略与学业成就的关系

以学习自我效能感和学习策略量表为工具,通过方差分析、相关分析和路径分析等方法,重点考察了学习自我效能感和学习策略这两个因素对学业成就的影响路径以及相互间的关系.发现中学生的学习自我效能感与学习策略间存在着显著的相关关系;学习自我效能感和学习策略对初中生的学业成就有显著回归效应,而学习策略对高中生的学业成就有显著回归效应;学习自我效能感可通过影响学习策略来间接影响学业成就.     

Bayesian Estimation for the Order of INAR(q) Mo del

In this paper, we consider the problem of determining the order of INAR(q) model on the basis of the Bayesian estimation theory. The Bayesian es-timator for the order is given with respect to a squared-error loss function. The consistency of the estimator is discussed. The results of a simulation study for the estimation method are presented.     

Objective Bayesian analysis of the Frechet stress–strength model

Several reference priors and a general form of matching priors are derived for a stress–strength system, and it is concluded that none of the reference priors is a matching prior. The study shows that the matching prior performs better than Jeffreys prior and reference priors in meeting the target coverage probabilities.     

Quantum chemical electron impact mass spectrum prediction for de novo structure elucidation: Assessment against experimental reference data and comparison to competitive fragmentation modeling

We investigate the success of the quantum chemical electron impact mass spectrum (QCEIMS) method in predicting the electron impact mass spectra of a diverse test set of 61 small molecules selected to be representative of common fragmentations and reactions in electron impact mass spectra. Comparison with experimental spectra is performed using the standard matching algorithms, and the relative ranking position of the actual molecule matching the spectra within the NIST‐11 library is examined. We find that the correct spectrum is ranked in the top two matches from structural isomers in more than 50% of the cases. QCEIMS, thus, reproduces the distribution of peaks sufficiently well to identify the compounds, with the RMSD and mean absolute difference between appropriately normalized predicted and experimental spectra being at most 9% and 3% respectively, even though the most intense peaks are often qualitatively poorly reproduced. We also compare the QCEIMS method to competitive fragmentation modeling for electron ionization, a training‐based mass spectrum prediction method, and remarkably we find the QCEIMS performs equivalently or better. We conclude that QCEIMS will be very useful for those who wish to identify new compounds which are not well represented in the mass spectral databases.     

Distance versus Capillary Flow Dynamics-Based Detection Methods on a Microfluidic Paper-Based Analytical Device (μPAD)

In recent years, there has been high interest in paper-based microfluidic sensors or microfluidic paper-based analytical devices (μPADs) towards low-cost, portable, and easy-to-use sensing for chemical and biological targets. μPAD allows spontaneous liquid flow without any external or internal pumping, as well as an innate filtration capability. Although both optical (colorimetric and fluorescent) and electrochemical detection have been demonstrated on μPADs, several limitations still remain, such as the need for additional equipment, vulnerability to ambient lighting perturbation, and inferior sensitivity. Herein, alternative detection methods on μPADs are reviewed to resolve these issues, including relatively well studied distance-based measurements and the newer capillary flow dynamics-based method. Detection principles, assay performance, strengths, and weaknesses are explained for these methods, along with their potential future applications towards point-of-care medical diagnostics and other field-based applications.     

Bayesian Analysis of Exafs Data

In this paper we demonstrate the use of Bayesian analysis methods for the analysis of EXAFS data. We will discuss the physical parameters that may be estimated by the method and demonstrate the applicability of the method to Molybdenum coordination compounds.     

FFLUX: Transferability of polarizable machine‐learned electrostatics in peptide chains

The fully polarizable, multipolar, and atomistic force field protein FFLUX is being built from machine learning (i.e., kriging) models, each of which predicts an atomic property. Each atom of a given protein geometry needs to be assigned such a kriging model. Such a knowledgeable atom needs to be informed about a sufficiently large environment around it. The resulting complexity can be tackled by collecting the 20 natural amino acids into a few groups. Using substituted deca‐alanines, we present the proof‐of‐concept that a given atom's charge can be modeled by a few kriging models only. © 2017 Wiley Periodicals, Inc.     

Complex dynamics in equilibrium asset pricing models with boundedly rational,heterogeneous agents

We study a simple model based upon the Lucas framework where heterogeneous agents behave rationally in a fully intertemporal setting but do not know other investors' personal preferences, wealth or investment portfolios. As a consequence, agents initially do not know the equilibrium asset pricing function and must make guesses, which they update via adaptive learning with constant gain. We demonstrate that even in this simple environment the economy can, depending on parameters, exhibit either stable convergence to equilibrium, or chaotic dynamical behavior of asset prices and trading volume without converging to the rational expectations equilibrium of the Lucas model. This contradicts the assertion that the Lucas model is stable in the face of modest deviations from the strong assumptions required to compute the equilibrium. © 2013 Wiley Periodicals, Inc. Complexity 19: 38–55, 2014