Results 81 to 90 of about 40,934 (281)
A method of estimating the average derivative: the multivariate case [PDF]
The paper uses local linear regression to estimate the ``direct'' Average Derivative \delta = E(D[m(x)]), where m(x) is the regression function. The estimate of \delta is the weighted average of local slope estimates. We prove the asymptotic normality of
Banerjee, Anurag N.
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Journal of Consumer Behaviour, EarlyView.ABSTRACT This study examines the impact of self‐checkout technology implementation on B2B customer shopping behavior using a novel methodological approach that combines propensity score matching with difference‐in‐differences analysis on actual point‐of‐sale transaction data.
Jindřich Špička +1 more
wiley +1 more source
Nonparametric bias reduction of diffusion function in stochastic volatility models
AIMS MathematicsThis paper proposed a novel bias correction method based on nonparametric kernel estimator of the diffusion function in stochastic volatility models. In the case of fixed time span, the asymptotic bias of kernel estimation and the proposed nonparametric ...
Yunyan Wang +2 more
doaj +1 more source
The Filament Extension Atomization Process for Powder Production of Elastic Fluids
Chemie Ingenieur Technik, EarlyView.Filament extension atomization is a promising technique for spraying a wide range of materials, enabling narrow droplet size distributions. This study examines the behavior of various fluids and suspensions to define application limits and identify optimal operating conditions.
Moritz Neukötter +4 more
wiley +1 more source
Omnibus Tests for Multivariate Normality of Observations and Residuals [PDF]
This paper provides omnibus tests for multivariate normality of both observations and residuals. They are derived by considering as the alternatives to the multivariate normal a class of maximum-entropy distributions studied elsewhere by the author.
Urzúa, Carlos M.
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Optimal model‐based design of experiments for parameter precision: Supercritical extraction case
The Canadian Journal of Chemical Engineering, EarlyView.Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent ...
Oliwer Sliczniuk, Pekka Oinas
wiley +1 more source
Maximum pseudo-likelihood estimator for nearest-neighbours Gibbs point processes
, 2006 This paper is devoted to the estimation of a vector parametrizing an energy function associated to some "Nearest-Neighbours" Gibbs point process, via the pseudo-likelihood method.
Billiot, Jean-Michel +2 more
core +1 more source
Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Predicting cervical cancer DNA methylation from genetic data using multivariate CMMP
Canadian Journal of Statistics, EarlyView.Abstract Epigenetic modifications link the environment to gene expression and play a crucial role in tumour development. DNA methylation, in particular, is gaining attention in cancer research, including cervical cancer, the focus of this study.
Hang Zhang +5 more
wiley +1 more source
Asymptotic distributions of robust shape matrices and scales [PDF]
It has been frequently observed in the literature that many multivariate statistical methods require the covariance or dispersion matrix ∑ of an elliptical distribution only up to some scaling constant.
Frahm, Gabriel
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