Results 61 to 70 of about 130,311 (282)

The impact of mulberry leaf extract at three different levels on reducing the glycemic index of white bread.

PLoS ONE, 2023
In this study, the influences of mulberry leaf extract (MLE) addition on the physicochemical properties including the specific volume, texture and sensory features of white bread (WB) were evaluated by the sensory analysis technology.
Fangli Ding, Qing Wang, Chen Xie, Meng Wang, Lu Zhang, Ming Gao, Zongling Yang, Jianrui Ma, Xiaodong Shi, Wei Chen, Shenglin Duan, Peng Yuan, Yali Li, Xishan Ma, Yimin Wu, Jia Liu, Xiaowen Feng, Qingli Cheng, Zichun Wang, Xuyan Li, Jingmei Huang   +20 more
doaj   +1 more source

Evaluating Maximum Likelihood Estimation Methods to Determine the Hurst Coefficient [PDF]

, 1999
A maximum likelihood estimation method implemented in S-PLUS (S-MLE) to estimate the Hurst coefficient (H) is evaluated. The Hurst coefficient, with 0.5\u3cHS-MLE was developed to estimate H for fractionally differenced (fd) processes.
Bassingthwaighte, J. B., Kendziorski, Christina Marie, Tonellato, Peter J.   +2 more
core   +1 more source

A partial envelope approach for modelling multivariate spatial‐temporal data

Canadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja, Wenbo Wu, Victor De Oliveira, Keying Ye   +3 more
wiley   +1 more source

Statistical aspects of the fractional stochastic calculus

, 2007
We apply the techniques of stochastic integration with respect to fractional Brownian motion and the theory of regularity and supremum estimation for stochastic processes to study the maximum likelihood estimator (MLE) for the drift parameter of ...
Tudor, Ciprian A., Viens, Frederi G.
core   +6 more sources

Seizure forecasting with epilepsy cycles: On the causality of forecasting pipelines

Epilepsia, EarlyView.
Abstract Objective Seizure risk is modulated by multiscale brain rhythms. Previous studies using cycles in electroencephalography, heart rate, and wearable data suggest the possibility of forecasting seizures days in advance. However, they commonly rely on methods requiring (days of) information from time points beyond the moment of forecast (noncausal
Hongliu Yang, Jens Müller, Sotirios Kalousios, Georg Leonhardt, Matthias Dümpelmann, Andreas Schulze‐Bonhage, Ronald Tetzlaff   +6 more
wiley   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Assessing the role of civil society in poverty alleviation: A case study of Amathole district in the Eastern Cape province of South Africa

The Journal for Transdisciplinary Research in Southern Africa, 2019
The purpose of this study was to conduct an assessment of the role of civil society organisations (CSOs) in poverty alleviation, with a particular focus on three CSOs operating in the Amathole district of the Eastern Cape province.
Xolisile G. Ngumbela, Thozamile R. Mle
doaj   +1 more source

Maximum Likelihood Estimation of Functionals of Discrete Distributions

, 2017
We consider the problem of estimating functionals of discrete distributions, and focus on tight nonasymptotic analysis of the worst case squared error risk of widely used estimators.
Han, Yanjun, Jiao, Jiantao, Venkat, Kartik, Weissman, Tsachy   +3 more
core   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source

Bounds for the normal approximation of the maximum likelihood estimator

, 2016
While the asymptotic normality of the maximum likelihood estimator under regularity conditions is long established, this paper derives explicit bounds for the bounded Wasserstein distance between the distribution of the maximum likelihood estimator (MLE)
Anastasiou, Andreas, Reinert, Gesine
core   +1 more source