Results 131 to 140 of about 194 (182)
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
A spectral analysis extension to DEMATEL for strategic leverage points identification
Abstract Efforts to intervene in complex systems often emphasize influential factors, yet system behavior is equally shaped by the relationships among them. Methods such as Decision‐Making Trial and Evaluation Laboratory (DEMATEL) map causal structures but remain descriptive and do not identify which relationships provide the greatest leverage for ...
Pavlos Delias, Kerasia Kalkitsa
wiley +1 more source
A Unified Approach to Estimating Production Functions: Proxy Variables and Dynamic Panel Data
ABSTRACT We propose a new approach to production function estimation that integrates the strengths of the proxy‐variable (PV) and dynamic panel data (DPD) methods. Our framework augments the set of instruments for the level equation in Blundell and Bond [8] with a Berkson‐type instrument motivated by economic theory, following Olley and Pakes [28 ...
Jose Miguel Abito +1 more
wiley +1 more source
ABSTRACT Lucid dreaming, defined as the experience of becoming aware of dreaming while dreaming, offers a unique window into a state of consciousness characterised by a blending of the sensory vividness of REM sleep with the self‐awareness of wakefulness. While past functional imaging has shed light on the neural activity supporting lucid dreaming, the
Nicola De Pisapia +4 more
wiley +1 more source
Robust CDF‐Filtering of a Location Parameter
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania +2 more
wiley +1 more source
Measure‐valued processes for energy markets
Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero +3 more
wiley +1 more source
Solving Stochastic Climate‐Economy Models: A Deep Least‐Squares Monte Carlo Approach
ABSTRACT Stochastic versions of recursive integrated climate‐economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of state variables and stochastic shocks increases, solving these models via deterministic grid‐based dynamic programming (e.g., value‐function iteration/projection ...
Aleksandar Arandjelović +4 more
wiley +1 more source
Tax Progressivity, Public Debt, and Growth in a Neo‐Kaleckian Model
ABSTRACT We develop a neo‐Kaleckian growth‐and‐distribution model featuring two classes of workers and a progressive income tax. Two fiscal closures are considered: balanced budgets and deficit financing via public debt. We study the responses to shocks, including changes in functional income distribution, and assess how tax progressivity alters demand
Tailiny Ventura +2 more
wiley +1 more source
Aggregation and the Structure of Value
ABSTRACT Roughly, the view I call “Additivism” sums up value across time and people. Given some standard assumptions, I show that Additivism follows from two principles. The first says that how lives align in time cannot, in itself, matter. The second says, roughly, that a world cannot be better unless it is better within some period or another.
Weng Kin San
wiley +1 more source
Is A Little Learning Dangerous?
ABSTRACT I argue that a little learning is often dangerous even for ideal reasoners who are operating in extremely simple scenarios and know all the relevant facts about how the evidence is generated. More precisely, I show that, on many plausible ways of assigning value to a credence in a hypothesis H, ideal Bayesians should sometimes expect other ...
Bernhard Salow
wiley +1 more source

