Universality for the largest eigenvalue of sample covariance matrices with general population by Bao, Zhigang, Pan, Guangming, Zhou, Wang

“…This paper is aimed at deriving the universality of the largest eigenvalue of a class of high-dimensional real or complex sample covariance matrices of the form WN = Σ 1 /2 XX* Σ 1/2. …”
Get full text
Get full text

15.075 Applied Statistics, Spring 2003 by Newton, Elizabeth

Get full text

Inference for autoregressive and moving average models with extreme value distribution via simulation study by Samuel, Bako Sunday

“…Time series analysis has emerged as one of the most important statistical discipline and it has been applied in different fields over the years. …”
Get full text

Challenges and Solution of Online Learning and Assessment Amidst the COVID-19 Pandemic: A Case Study in Universiti Utara Malaysia (S/O 14793) by Mohd Nordin, Nur Rasyidah, Omar, Wafa, Mohd Ridzuan, Iliya Nurul Iman

“…However, with the pandemic, language instructors are forced to utilize online platforms to teach and assess the students. …”
Get full text

Factors Influencing Students Intention to Choose Career of Halal Food Industry in Malaysia using Theory of Planned Behavior by Abu Bakar, Nashirah, Rosbi, Sofian, Haji Hashim, Hydzulkifli, Che Arshad, Noraziah

“…The value of Cronbach’s alpha statistical test for measuring internal reliability is larger than 0.7 for all four variables. …”
Get full text

Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling by Guth, Stephen, Katsidoniotaki, Eirini, Sapsis, Themistoklis P.

“…Accurately determining hydrodynamic force statistics is crucial for designing offshore engineering structures, including offshore wind turbine foundations, due to the significant impact of nonlinear wave–structure interactions. …”
Get full text

Towards haptic intelligence in robots by learning from demonstration by Turlapati Sri Harsha

“…This is motivated by the observation that classical kinaesthetic teaching by physically guiding the robot through a particular task is not sufficient for learning the haptics of the task. This is because the forces the human applies on the robot are also recorded along with the task forces, thus "corrupting" any useful strategy. …”
Get full text

Theoretical study of spermatozoa sorting by dielectrophoresis or magnetophoresis with supervised learning by Koh, James Boon Yong

“…The flagellum waveform is prescribed analytically, and subsequently solved from force and moment balance. The hydrodynamic force acting on the sperm is computed using Resistive Force Theory as well as Slender Body Theory, and the resulting velocity is compared qualitatively and quantitatively. …”
Get full text
Get full text

Exploratory Survey on UUM Student’s Acceptance Towards the Founding of Waqf Institution For Education by Omar, Hydzulkifli Hashim, Abu Bakar, Azizi, Basary, Noor Faezah, Shuib, Mohd Sollehudin, Yusuff, Noraini

“…All the data are analysed using software of Statistical Package for Social Science (SPSS) by conducting statistical method namely, Independent Samples T-test, Analysis of Variance (ANOVA), Pearson Corellation and Multiple Linear Regression analysis to achieve the objectives of this research. …”
Get full text

Macroeconomic and Firm-Specific Effects on Islamic Deposits Sustainability by Ab Rahman, Sazana, Ahmad, Nor Hayati, Che Arshad, Noraziah

Get full text
Get full text

Adoption of ZakaTech in the Time of COVID-19: Cross-Country and Gender Differences by Nashwan, Saeed Awadh, Ismaiel, Abdelhamid Elsayed A., Muneeza, Aishath, Isa, Mohamad Yazid

“…Findings – By analyzing both Saudi and Egyptian samples, the authors found that all UTAUT constructs are statistically significant, except for effort expectancy in Egypt. …”
Get full text

Forecasting Singapore’s pharmaceutical industry using time series models. by Lee, Kai Wee., Simandjuntak, Daniel Perdana., Zhuo, Yaohong.

Get full text

Refining learning models in grammatical inference by Wang, Xiangrui

“…Grammatical inference is a branch of computational learning theory that attacks the problem of learning grammatical models from string samples. …”
Get full text

A study on open set recognition methods by Sun, Xin

“…We combine the proposed loss function with the Softmax loss function, which is used in most Convolutional Neural Networks (CNNs), to force learned features in different classes to be close to different centroids for Gaussian modeling. …”
Get full text

Investigating the EM performance of building materials for mid-band 5G in urban built environment: an exploratory study by Ng, Sean Jake Peng

“…From the analysis of the free-space transmission coefficients (|S21|) data, samples from the 2 wt% Fe2O3 treatment group demonstrated statistically significant mean improvements in microwave transparency (up to 2.28 dB) and 100% fractional bandwidth performance across the 3.40 to 3.60 GHz frequency range. …”
Get full text

Neural and psychological correlates of stuttering by Demirel, B

“…Despite this relatively large sample size, we found no significant group differences at a strict statistical threshold (Z > 3.1). …”

Effect of educational intervention on the intention to provide family-centered care among selected hospitals’ paediatric nurses in Tehran, Iran by Rostami, Forouzan

“…Descriptive and multivariate statistics (repeated measures ANOVA) were used for analysing the data. …”
Get full text

Reliability analysis and data driven modelling of railway component failure by Wang, Jinlong

“…The one-dimensional time-to-failure type data sets in the first three cases were modeled by Weibull distribution models to characterize the reliability. Such statistical models are under some distribution assumptions which may not be fully satisfied in practice, but the models can be fitted with limited data samples and their interpretabilities are high. …”
Get full text

Efficient Bayesian estimation and use of cut posterior in semiparametric hidden Markov models by Moss, D, Rousseau, J

Advances in Sparse and Low Rank Matrix Optimization for Machine Learning Applications by Johnson, Nicholas André G.

“…This thesis advances both the theory and application of sparse and low rank matrix optimization, focusing on problems that arise in statistics and machine learning. …”
Get full text