Natural language processing

TL;DR: The purpose of this article is to clarify the distinction between explanatory and predictive modeling, to discuss its sources, and to reveal the practical implications of the distinction to each step in the modeling process.

TL;DR: This paper developed a dynamic stochastic general equilibrium (DSGE) model for an open economy, and estimate it on Euro area data using Bayesian estimation techniques, incorporating several open economy features, as well as a number of nominal and real frictions that have proven important for the empirical fit of closed economy models.

TL;DR: To show that predictive analytics and explanatory statistical modeling are fundamentally disparate, it is shown that they are different in each step of the modeling process and these differences translate into different final models, so that a pure explanatory statistical model is best tuned for testing causal hypotheses and a pure predictive models is best in terms of predictive power.

TL;DR: In this paper, the authors define an ontological trichotomy, event-process-state, which is defined as those occurrences that are inherently countable, i.e., there was at least one or more capsizing of a boat by a vessel.

TL;DR: A Semantic Theory of "NP-movement" Dependencies and a Phrase Structure Account of Scandinavian Extraction Phenomena.

TL;DR: Transformational grammars for natural languages, as currently envisaged, deploy a large number of devices: complex symbols, base rules, rule schemata, lexical insertion rules, Lexical redundancy rules, movement rules, coindexing procedures, binding conventions, local and nonlocal filters, case marking conventions, feature percolation, constraints on movement, and so on.