Results 71 to 80 of about 2,081 (228)

Bayesian inference for dynamic Q matrices and attribute trajectories in hidden Markov diagnostic classification models

open access: yesBritish Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Hidden Markov diagnostic classification models capture how students' cognitive attributes evolve over time. This paper introduces a Bayesian Markov chain Monte Carlo algorithm for diagnostic classification models that jointly estimates time‐varying Q matrices, latent attributes, item parameters, attribute class proportions and transition ...
Chen‐Wei Liu
wiley   +1 more source

On the 𝑞-Bernoulli Numbers and Polynomials with Weight 𝜶

open access: yesAbstract and Applied Analysis, 2011
We present a systemic study of some families of higher-order 𝑞-Bernoulli numbers and polynomials with weight 𝛼. From these studies, we derive some interesting identities on the 𝑞-Bernoulli numbers and polynomials with weight 𝛼.
T. Kim, J. Choi
doaj   +1 more source

Numerical Semigroups, Cyclotomic Polynomials, and Bernoulli Numbers [PDF]

open access: yesThe American Mathematical Monthly, 2014
13 pages, 2 diagrams, expository paper to appear in American Mathematical Monthly, mathematical improvements in section on symmetric numerical semigroups, LLL-diagram material added, many minor ...
openaire   +2 more sources

Regularized reduced rank regression for mixed predictor and response variables

open access: yesBritish Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract In this paper, we introduce the Generalized Mixed Regularized Reduced Rank Regression model (GMR4), an extension of the GMR3 model designed to improve performance in high‐dimensional settings. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables, while also allowing for mixed‐type predictors through optimal ...
Lorenza Cotugno   +2 more
wiley   +1 more source

The U‐shaped effect of logic multiplicity on organizational performance: Evidence from the US healthcare industry

open access: yesEuropean Management Review, EarlyView.
Abstract We investigate the effect of logic multiplicity on organizational performance and hypothesize that logics may impact performance in view of their sheer number. We further propose that the market logic embedded in the for‐profit legal form can positively moderate the impact of multiple logics on performance.
Francesca Capo   +3 more
wiley   +1 more source

Special Numbers and Polynomials Including Their Generating Functions in Umbral Analysis Methods

open access: yesAxioms, 2018
In this paper, by applying umbral calculus methods to generating functions for the combinatorial numbers and the Apostol type polynomials and numbers of order k, we derive some identities and relations including the combinatorial numbers, the Apostol ...
Yilmaz Simsek
doaj   +1 more source

A note on Carlitz q-Bernoulli numbers and polynomials [PDF]

open access: yesAdvances in Difference Equations, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, Daeyeoul, Kim, Min-Soo
openaire   +1 more source

Twisted (h,q)-Bernoulli numbers and polynomials related to twisted (h,q)-zeta function and L-function☆

open access: yes, 2006
In this paper, by using q-Volkenborn integral, we construct new generating functions of the new twisted ( h , q ) -Bernoulli polynomials and numbers. By applying the Mellin transformation to these generating functions, we obtain integral representations ...
Y. Simsek
semanticscholar   +1 more source

Addressing Bias in Non‐Probability Fisheries Surveys Using Multilevel Regression and Poststratification Approaches

open access: yesFish and Fisheries, EarlyView.
ABSTRACT Quantifying harvest of fish stocks is challenging as census data are often unavailable, so surveys are required. Traditional probability‐based surveys use random sampling to obtain representative data that can be scaled to estimate total impact.
Zachary Radford   +8 more
wiley   +1 more source

A Horse Race of Machine‐Learning Methods to Predict Banking Crises

open access: yesInternational Finance, EarlyView.
ABSTRACT To examine if one machine‐learning model can consistently elucidate financial vulnerabilities, both over time and across levels of development, this paper applies 13 machine‐learning algorithms to evaluate comparative forecasting performance across several banking crises.
Emile du Plessis
wiley   +1 more source

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