When is a statistical dependency between two variables best explained by the supposition that one of these variables causes the other, as opposed to the supposition that there is a (possibly unmeasured) common cause acting on both variables? In this paper, we describe an approach towards model specification developed more fully in our book Discovering Cuud Structure, and illustrate its applicat...

Model selection, the task of selecting a statistical model from a certain model class given data, is an important problem in statistical learning. From another perspective model selection can also be viewed as learning a single distribution, where the parameter space includes a discrete structure parameter s which imposes further constraints on the remaining parameterization of that model, so t...

This article examines the theoretical status of latent variables as used in modern test theory models. First, it is argued that a consistent interpretation of such models requires a realist ontology for latent variables. Second, the relation between latent variables and their indicators is discussed. It is maintained that this relation can be interpreted as a causal one but that in measurement ...

We present the Hybrid Predicate Calculus (HPC), a hybrid logical system which incorporates a fairly conventional first-order predicate calculus, but which also include elements of modal logic and relational algebra. A special effort has been made to produce a (syntactically and semantically) well-integrated whole, rather than just a disjoint union. Our calculus, from a formal point of view, is ...

We demonstrate a simple and robust program transformation technique that can improve asymptotic time complexity of datamanipulating programs (e.g., produce a linear-time list reversal function from the obvious quadratic one). In the version of the present paper, it applies to monadic inductive datatypes and can be stated in two flavors, through a datatype representation, with an explicit (“froz...

An attractive format for semantics is that in which composite expressions are built up from atomic ones by means of the operation of concatenation and the concatenation XY expresses the application of a function denoted by X to an argument denoted by Y . The use of relative pronouns presents an obstacle to this form of compositional semantics, since the reference of a relative pronoun in one co...

Variational inference transforms posterior inference into parametric optimization thereby enabling the use of latent variable models where it would otherwise be impractical. However, variational inference can be finicky when different variational parameters control variables that are strongly correlated under the model. Traditional natural gradients that use the variational approximation fail t...

Intuition and insight share similar cognitive and neural basis. Though, there are still some essential differences between the two. Here in this short review, we discriminated between intuition, and insight in two aspects. First, intuition, and insight are toward different aspects of information processing. Whereas intuition involves judgment about "yes or no," insight is related to "what" is t...

The subjective Aha! experience that problem solvers often report when they find a solution has been taken as a marker for insight. If Aha! is closely linked to insightful solution processes, then theoretically, an Aha! should only be experienced when the correct solution is found. However, little work has explored whether the Aha! experience can also accompany incorrect solutions ("false insigh...

In conventional structural equation models, all latent variables and indicators vary between units (typically subjects) and are assumed to be independent across units. The latter assumption is violated in multilevel settings where units are nested in clusters, leading to within-cluster dependence. Different approaches to extending structural equation models for such multilevel settings are exam...