30,408 research outputs found
A discontinuity in pattern inference
This paper examines the learnability of a major subclass
of E-pattern languages – also known as erasing or extended pattern languages
– in Gold’s learning model: We show that the class of terminal-free
E-pattern languages is inferrable from positive data if the corresponding
terminal alphabet consists of three or more letters. Consequently, the
recently presented negative result for binary alphabets is unique
Exact detection of direct links in networks of interacting dynamical units
Authors NR, EB-M, CG, and MSB acknowledge the Scottish Universities Physics Alliance (SUPA). EB-M and MSB also acknowledge the Engineering and Physical Science Research Council (EPSRC) project Ref. EP/I032 606/1. ACM and CM acknowledge the LINC project (FP7-PEOPLE-2011-ITN, grant no. 289447). ACM also aknowledges PEDECIBA and CSIC(Uruguay). CM also acknowledges grant FIS2012–37655-C02–01 from the Spanish MCI, grant 2009 SGR 1168, and the ICREA Academia programme from the Generalitat de Catalunya.Peer reviewedPublisher PD
Sequential Specification Tests to Choose a Model: A Change-Point Approach
Researchers faced with a sequence of candidate model specifications must
often choose the best specification that does not violate a testable
identification assumption. One option in this scenario is sequential
specification tests: hypothesis tests of the identification assumption over the
sequence. Borrowing an idea from the change-point literature, this paper shows
how to use the distribution of p-values from sequential specification tests to
estimate the point in the sequence where the identification assumption ceases
to hold. Unlike current approaches, this method is robust to individual errant
p-values and does not require choosing a test level or tuning parameter. This
paper demonstrates the method's properties with a simulation study, and
illustrates it by application to the problems of choosing a bandwidth in a
regression discontinuity design while maintaining covariate balance and of
choosing a lag order for a time series model
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