Results 121 to 130 of about 61,972 (313)

Expansion of multivariate polynomials in products of univariate orthogonal polynomials: discrete case

Journal of Computational and Applied Mathematics, 2001
The aim of this paper is to present a method to apply difference operators on series of products of classical orthogonal polynomials of discrete variables. At first the authors remind of the application of partial differential operators on series of classical orthogonal polynomials basing on the hypergeometric approach to orthogonal polynomials given ...
Rebillard, L., Ronveaux, André
openaire   +2 more sources

Effects of Aerobic and Strength‐Based Exercise on Consumer Preference for Protein

Agricultural Economics, EarlyView.
ABSTRACT The role of protein consumption in adaptations to physical exercise is well documented in prior research. However, little is known about how physical exercise and associated protein needs impact consumers’ protein demand. This study pairs matching methods with discrete choice experiments to estimate the impacts of physical exercise on ...
Justin D. Bina
wiley   +1 more source

Modelling non‐linear psychological processes: Reviewing and evaluating non‐parametric approaches and their applicability to intensive longitudinal data

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Psychological concepts are increasingly understood as complex dynamic systems that change over time. To study these complex systems, researchers are increasingly gathering intensive longitudinal data (ILD), revealing non‐linear phenomena such as asymptotic growth, mean‐level switching, and regulatory oscillations.
Jan I. Failenschmid, Leonie V. D. E. Vogelsmeier, Joris Mulder, Joran Jongerling   +3 more
wiley   +1 more source

Some Families of Orthogonal Polynomials of a Discrete Variable and their Applications to Graphs and Codes [PDF]

, 2009
M. Cámara, J. Fàbrega, M.A. Fiol, E. Garriga   +3 more
openalex   +1 more source

Reduced rank regression for mixed predictor and response variables

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract In this paper, we propose the generalized mixed reduced rank regression method, GMR3 for short. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables. The predictor variables can be a mix of binary, nominal, ordinal and numeric variables. For dealing with the categorical predictors we use optimal scaling.
Mark de Rooij, Lorenza Cotugno, Roberta Siciliano   +2 more
wiley   +1 more source

DCKTKT: A New Discrete Cosine-Krawtchouk-Tchebichef Transform

Journal of Engineering
Real-world signals are often intricate and difficult to analyze. Therefore, to facilitate the analysis of signal components, the researchers represent the signal in different domains (transform domain), providing a new perspective and offering ...
Mariam Taha Yaseen, Sadiq H. Abdulhussain   +1 more
doaj   +1 more source

Speed Bump and Stock Market Quality: Evidence From NYSE American

Financial Management, EarlyView.
ABSTRACT Should trading speed of high‐frequency traders be regulated? Using the data from the New York Stock Exchange American, this paper examines the impact of a speed bump on market liquidity and price discovery. Our results indicate that the use of a speed bump can lower the costs of adverse selection through reducing informed trading.
Bo Liu, Ke Xu
wiley   +1 more source

The reproducing kernel structure arising from a combination of continuous and discrete orthogonal polynomials into Fourier systems [PDF]

, 2006
Luís Daniel Abreu
openalex   +1 more source

Evaluating Allocations of Opportunities

International Economic Review, EarlyView.
ABSTRACT This paper provides a robust criterion for comparing lists of probability distributions—interpreted as allocations of opportunities—faced by different social groups. We axiomatically argue in favor of comparing those lists of probability distributions on the basis of a uniform—among groups—valuation of their expected utility.
Francesco Andreoli, Mathieu Faure, Nicolas Gravel, Tista Kundu   +3 more
wiley   +1 more source

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source