Results 51 to 60 of about 3,425 (184)
An extension of the basic local independence model to multiple observed classifications
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The basic local independence model (BLIM) is appropriate in situations where populations do not differ in the probabilities of the knowledge states and the probabilities of careless errors and lucky guesses of the items. In some situations, this is not the case. This work introduces the multiple observed classification local independence model
Pasquale Anselmi +8 more
wiley +1 more source
LETTER Time Series Prediction Using an Interval Arithmetic FIR Network
, 2005 —We present an interval arithmetic neural network based on the FIR (Finite Impulse Response) network to improve the prediction power and flexibility. The model for the system is obtained by modifying the dynamics of the FIR network to incorporate the ...
Tae-wan Ryu, Ho Joon Kim
core
Reliability measures in knowledge structure theory
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract In knowledge structure theory (KST) framework, this study evaluates the reliability of knowledge state estimation by introducing two key measures: the expected accuracy rate and the expected discrepancy. The accuracy rate quantifies the likelihood that the estimated knowledge state aligns with the true state, while the expected discrepancy ...
Debora de Chiusole +3 more
wiley +1 more source
Development Of A Finite Element Analysis Program Based On Interval Arithmetic
, 1999 The purpose of the research project was to develop a finite element program based on interval, rather than floating point arithmetic. Finite element programs are used by designers to model and refine a design on the computer before an expensive prototype
Fritz, Frank M., Frank M. Fritz
core
Large subsets of Euclidean space avoiding infinite arithmetic progressions
, 2023 It is known that if a subset of $\mathbb{R}$ has positive Lebesgue measure, then it contains arbitrarily long finite arithmetic progressions. We prove that this result does not extend to infinite arithmetic progressions in the following sense: for each $\
Kohut, Hannah +2 more
core
Register‐Efficient Linear‐Time Evaluation in the Bernstein Basis
Computer Graphics Forum, EarlyView.Abstract We investigate the evaluation of points and derivatives of Bézier curves and surfaces on modern architectures, focusing on performance and guided by numerical error bounds. While the de Casteljau algorithm remains the reference for numerical robustness, its linear working‐set size imposes substantial register pressure on GPUs.
Gábor Valasek, Anna Lili Horváth
wiley +1 more source
Interval oriented multi-section techniques for global optimization
, 2009 This paper deals with two different optimization techniques to solve the bound-constrained nonlinear optimization problems based on division criteria of a prescribed search region, finite interval arithmetic and interval ranking in the context of a ...
Bhunia, A.K., Karmakar, S., Mahato, S.K.
core +1 more source
The big impact of small change: Fresh estimates of English wheat market integration, 1693–1893
The Economic History Review, EarlyView.Abstract Using existing and new price data sets, we provide the first estimates of market integration across England over the entire 200 years of the industrial revolution. We document a significant, though not huge, integration improvement for markets furthest from London. Full integration was achieved by the 1830s. Our price data sets vary in quality
Liam Brunt, Edmund Cannon
wiley +1 more source
Discharge‐Targeted Hydraulic Tomography to Quantify and Locate Aquifer Discharge
Groundwater, EarlyView.Abstract Quantifying and localizing groundwater discharge is inherently difficult. It requires knowledge about hydraulic conductivity and the hydraulic gradient on the scale of interest. Conventional hydraulic testing, such as pumping tests, may fail in the presence of heterogeneity and complex structural boundaries.
Konstantin Drach +2 more
wiley +1 more source
On Integral Priors for Multiple Comparison in Bayesian Model Selection
International Statistical Review, EarlyView.Summary Noninformative priors constructed for estimation purposes are usually not appropriate for model selection and testing. The methodology of integral priors was developed to get prior distributions for Bayesian model selection when comparing two models, modifying initial improper reference priors. We propose a generalisation of this methodology to
Diego Salmerón +2 more
wiley +1 more source