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12
A Field Guide to Recent Work on the Foundations of Statistical Mechanics
 FORTHCOMING IN DEAN RICKLES (ED.): THE ASHGATE COMPANION TO CONTEMPORARY PHILOSOPHY OF PHYSICS. LONDON: ASHGATE.
, 2008
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Nearly Optimal Tests when a Nuisance Parameter is Present Under the Null Hypothesis
, 2012
"... This paper considers nonstandard hypothesis testing problems that involve a nuisance parameter. We establish a bound on the weighted average power of all valid tests, and develop a numerical algorithm that determines a feasible test with power close to the bound. The approach is illustrated in six a ..."
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This paper considers nonstandard hypothesis testing problems that involve a nuisance parameter. We establish a bound on the weighted average power of all valid tests, and develop a numerical algorithm that determines a feasible test with power close to the bound. The approach is illustrated in six applications: inference about a linear regression coefficient when the sign of a control coefficient is known; small sample inference about the difference in means from two independent Gaussian samples from populations with potentially different variances; inference about the break date in structural break models with moderate break magnitude; predictability tests when the regressor is highly persistent; inference about an interval identified parameter; and inference about a linear regression coefficient when the necessity of a control is in doubt.
Approximation Algorithms for Finding the Optimal Bridge Connecting Two Simple Polygons
, 2003
"... Given two simple polygons P and Q we define the weight of a bridge (p; q), with p 2 ffi(P ) and q 2 ffi(Q), where ffi() defines the boundary of the polygon, between the two polygons as gd(p; P )+d(p; q)+gd(q; Q) where d(p; q) is the Euclidean distance between the points p and q, and gd(a; A) is t ..."
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Given two simple polygons P and Q we define the weight of a bridge (p; q), with p 2 ffi(P ) and q 2 ffi(Q), where ffi() defines the boundary of the polygon, between the two polygons as gd(p; P )+d(p; q)+gd(q; Q) where d(p; q) is the Euclidean distance between the points p and q, and gd(a; A) is the geodesic distance between a and its geodesic farthest neighbor on A. An optimal bridge (of minimum weight) can be found in O(n log n) time as described in [13]. We present an approximation scheme that, given any positive integer k, constructs a bridge with objective function value within (1 + ) of optimal in O(kn log kn) time, thus solving an open problem stated in [10]. We also present a fully polynomial time approximation scheme that for any ffl ? 0 generates a bridge with objective function within ffl of optimal in O(kn log kn) time, where k = 2 d e. In contrast to the exact algorithm given in [13], our algorithm does not use complicated data structures and is amenable to efficient implementations. We also show that the claim of [13] that if (p; q) is the optimal bridge, then gd(p; q) = d(p; q) is incorrect.
Experimental Economics: Some Methodological Notes
, 2009
"... The aim of this work is presenting in a selfcontained paper some methodological aspects as they are received in the current experimental literature. The purpose has been to make a critical review of some very influential papers dealing with methodological issues. In other words, the idea is to have ..."
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The aim of this work is presenting in a selfcontained paper some methodological aspects as they are received in the current experimental literature. The purpose has been to make a critical review of some very influential papers dealing with methodological issues. In other words, the idea is to have a single paper where people first approaching experimental economics can find summarised (some) of the most important methodological issues. In particular, the focus is on some methodological practises still debated in experimental literature, such as attainment of control in experimental settings, subject pool, incentive mechanisms, repeated trials and learning. The hope is that increasing awareness on some sharing methodologies will improve the robustness of results in this research
A METATHEORY OF A COGNITIVE MODEL OF LEARNING PROCESS BASED ON TRANSMULTIPLE ABILITIES
"... ABSTRACT Learning is a complex entity that involves not only the cognitive faculties such as thinking, reasoning and judgment, but also elicits conative and affective responses. In this paper, the authors examined three cognitive models of the learning process the modal model ..."
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ABSTRACT Learning is a complex entity that involves not only the cognitive faculties such as thinking, reasoning and judgment, but also elicits conative and affective responses. In this paper, the authors examined three cognitive models of the learning process the modal model
Approximation Algorithms for Finding the Optimal Bridge Connecting Two Simple Polygons
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Original Article The berth allocation problem: Optimizing
"... *Corresponding author. The berth scheduling problem deals with the assignment of vessels to berths in a marine terminal, with the objective to maximize the ocean carriers ’ satisfaction (minimize delays) and/or minimize the terminal operator’s costs. In the existing literature, two main assumptions ..."
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*Corresponding author. The berth scheduling problem deals with the assignment of vessels to berths in a marine terminal, with the objective to maximize the ocean carriers ’ satisfaction (minimize delays) and/or minimize the terminal operator’s costs. In the existing literature, two main assumptions are made regarding the status of a vessel: (a) either all vessels to be served are already in the port before the planning period starts, or (b) they are scheduled to arrive after the planning period starts. The latter case assumes an expected time of arrival for each vessel, which is a function of the departure time of the vessel from the previous port, the average operating speed and the distance between the two ports. Recent increases in fuel prices have forced ocean carriers to reduce current operating speeds, while stressing to terminal operators the need to maintain the integrity of their schedule. In addition, several collaborative efforts between industry and government agencies have been proposed, aiming to reduce emissions from marine vessels and port operations. In light of these issues, this article presents a berthscheduling policy to minimize vessel delayed
Structure ◮ Definition and visualization ◮ A glimpse of applications ◮ Geometry of the Stiefel manifolds ◮ Applications3 Collaborations
, 2009
"... The (compact) Stiefel manifold Vn,p is the set of all ptuples (x1,...,xp) of orthonormal vectors in Rn. If we turn ptuples into n × p matrices as follows (x1,...,xp) ↦ → [] x1 · · · xp, the definition becomes Vn,p = {X ∈ R n×p: X T X = Ip}. ..."
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The (compact) Stiefel manifold Vn,p is the set of all ptuples (x1,...,xp) of orthonormal vectors in Rn. If we turn ptuples into n × p matrices as follows (x1,...,xp) ↦ → [] x1 · · · xp, the definition becomes Vn,p = {X ∈ R n×p: X T X = Ip}.