98,238 research outputs found
Graphical models for marked point processes based on local independence
A new class of graphical models capturing the dependence structure of events
that occur in time is proposed. The graphs represent so-called local
independences, meaning that the intensities of certain types of events are
independent of some (but not necessarily all) events in the past. This dynamic
concept of independence is asymmetric, similar to Granger non-causality, so
that the corresponding local independence graphs differ considerably from
classical graphical models. Hence a new notion of graph separation, called
delta-separation, is introduced and implications for the underlying model as
well as for likelihood inference are explored. Benefits regarding facilitation
of reasoning about and understanding of dynamic dependencies as well as
computational simplifications are discussed.Comment: To appear in the Journal of the Royal Statistical Society Series
Learning Outcomes For Economists
Articulating thoughtful learning outcome statements for courses and majors improves teaching and learning and satisfies accreditation requirements. After reading this paper, economists will be able to construct learning outcome statements that guide and enhance teaching and learning in their courses and programs. We present a framework for developing learning outcomes based on a set of five fundamental competencies in economics. We then provide another public good, offering a complete set of learning outcomes for an introductory microeconomics course, which instructors can include in their syllabi. For additional guidance, we construct examples of lesson-specific learning outcomes as well
Reasoning about Independence in Probabilistic Models of Relational Data
We extend the theory of d-separation to cases in which data instances are not
independent and identically distributed. We show that applying the rules of
d-separation directly to the structure of probabilistic models of relational
data inaccurately infers conditional independence. We introduce relational
d-separation, a theory for deriving conditional independence facts from
relational models. We provide a new representation, the abstract ground graph,
that enables a sound, complete, and computationally efficient method for
answering d-separation queries about relational models, and we present
empirical results that demonstrate effectiveness.Comment: 61 pages, substantial revisions to formalisms, theory, and related
wor
Requirements modelling and formal analysis using graph operations
The increasing complexity of enterprise systems requires a more advanced
analysis of the representation of services expected than is currently possible.
Consequently, the specification stage, which could be facilitated by formal
verification, becomes very important to the system life-cycle. This paper presents
a formal modelling approach, which may be used in order to better represent
the reality of the system and to verify the awaited or existing system’s properties,
taking into account the environmental characteristics. For that, we firstly propose
a formalization process based upon properties specification, and secondly we
use Conceptual Graphs operations to develop reasoning mechanisms of verifying
requirements statements. The graphic visualization of these reasoning enables us
to correctly capture the system specifications by making it easier to determine if
desired properties hold. It is applied to the field of Enterprise modelling
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