This paper generalizes the authors’ inferential model (IM) framework for priorfree, posterior probabilistic inference about unknown parameters. This generalization is accomplished by focusing on an association model determined by the sampling distribution of a function of the data and parameter. The advantage is that the new association model is generally easier to work with than that determine...

Macromolecular structures calculated from nuclear magnetic resonance data are not fully determined by experimental data but depend on subjective choices in data treatment and parameter settings. This makes it difficult to objectively judge the precision of the structures. We used Bayesian inference to derive a probability distribution that represents the unknown structure and its precision. Thi...

Brain images are used both as scientific evidence and to illustrate the results of neuroimaging experiments. These images are apt to be viewed as photographs of brain activity, and in so viewing them people are prone to assume that they share the evidential characteristics of photographs. Photographs are epistemically compelling, and have a number of characteristics that underlie what I call th...

Given the recent and highly publicized scandals involving psychology researchers who cheated, the proliferation of articles on related topics is unsurprising. As an example, Simons et al. (2011) pointed out subtle ways in which researchers can increase their false positive rate above the nominal level of p < 0.05. From my perspective, a major limitation of the literature on cheating has been a ...

This paper describes a class of SQL injection attacks (SQLIA) where attackers can deduce information from the back-end database management system (DBMS) without transferring actual data. Instead, by using predetermined differentiation mechanism, information is being inferred piece by piece. Because of its widespread success, particularly in difficult situations where other SQLIA classes fail, u...

Inferential models (IMs) provide a general framework for prior-free, frequencycalibrated, posterior probabilistic inference. The fundamental idea is the use of unobservable auxiliary variables to describe the underlying uncertainty about the parameter of interest. When nuisance parameters are present, a marginalization step can reduce the dimension of the auxiliary variable, which in turn leads...

This paper examines downward price rigidity in Iranian house market and discusses whether this characteristic would result in an asymmetric relationship between house price and monetary policy. To test the downward house price rigidity the threshold GARCH model is employed. The asymmetric adjustment to monetary policy is examined using the asymmetric cointegration and error correction models. T...

in this research, a braiding-pultrusion production line is developed by modifying a conventional textile maypole braiding machine and adding it to a pultrusion line for production of braid-pultruded (bp) composite rods. in order to evaluate the mechanical properties of bp rods and study the effect of some braiding parameters, they were produced with different braid roving linear densities and b...