In the history of adoption research, subjective norm mostly remains as the unloved child, being significant in this analysis and not significant in that analysis. Already Davis et al. had to exclude subjective norm of the Technology Acceptance Model due to theoretical and measurement problems. Overall the results of subjective norm as an antecedent for behavioral intention in IS research are qu...

Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral contro...

This paper reviews the application of Gibbs sampling to a cointegrated VAR system. Aggregate imports and import prices for Belgium are modelled using two cointegrating relations. Gibbs sampling techniques are used to estimate from a Bayesian perspective the cointegrating relations and their weights in the VAR system. Extensive use of spectral analysis is made to get insight into convergence iss...

One of the key uses of causes is to explain why things happen. Explanations of specific events, like an individual’s heart attack on Monday afternoon or a particular car accident, help assign responsibility and inform our future decisions. Computational methods for causal inference make use of the vast amounts of data collected by individuals to better understand their behavior and improve thei...

When choosing the best method to undertake a biopsy of a lesion in the lung or mediastinum, it is important to consider the entire range of possible options, such as surgical, bronchoscopic/endoscopic, and radiologic techniques. Features to be considered include the anatomic location of the lesion, the amount of tissue needed, cost, availability of specific techniques, safety and risks, and exp...

Searching conformational ensembles of proteins remains a challenge in atomistic simulation of biomolecules. One approach to accelerate the protein sampling is to take advantage of rough energy surface from the coarse-grained model and, at the same time, to persist atomistic details from the all-atom model. Multiscale enhanced sampling (MSES) of all atoms and topology-based coarse-grained replic...

A number of techniques for probability sampling without replacement (SWOR) have been suggested, although it is not clear which method is consistently superior in terms of statistical efficiency. Rao and Bayless (1969) empirically studied the stability of estimators of the population total for a variety of methods of unequal probability SWOR when selecting two units per stratum. One of their maj...

An innovative approach to non-uniform sampling is proposed in this research paper specifically two engineering methods to sampling are proposed. Using results from statistics literature, an “optimal sampling” scheme is discussed. Information theoretic approach to nonuniform sampling formulated.

This paper presents a new approach to multiobjective optimization based on the principles of probabilistic uncertainty analysis. At the core of this approach is an efficient nonlinear multiobjective optimization algorithm, Minimizing Number of Single Objective Optimization Problems (MINSOOP), to generate a true representation of the whole Pareto surface. Results show that the computational savi...

The variational reconstruction theory from a companion paper finds a solution consistent with some linear constraints and minimizing a quadratic plausibility criterion. It is suitable for treating vector and multidimensional signals. Here, we apply the theory to a generalized sampling system consisting of a multichannel filterbank followed by a nonuniform sampling. We provide ready-made formula...