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

“…To achieve our objectives, a stationary autoregressive and moving average models with Gumbel distributed innovation is proposed and we characterise the short-term dependence among maxima, arising from light-tailed Gumbel distribution over a range of sample sizes with varying degrees of dependence. …”
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Multiscale approach to nematic liquid crystals via statistical field theory by Lu, Bing-Sui

“…We propose an approach to a multiscale problem in the theory of thermotropic uniaxial nematics based on the method of statistical field theory. …”
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Statistics and Probability Theory : In Pursuit of Engineering Decision Support / by Faber, M. H. (Michael Havbro), author 656113

“…The purpose of the book is to ensure that the reader will acquire the required theoretical basis and technical skills such as to feel comfortable with the theory of basic statistics and probability. Moreover, in this book, as opposed to many standard books on the same subject, the perspective is to focus on the use of the theory for the purpose of engineering model building and decision making. …”
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Dynamics of localized waves in one-dimensional random potentials : statistical theory of the coherent forward scattering peak by Lee, Kean Loon, Miniatura, Christian, Grémaud, Benoît

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3D reconstruction of building models based on 2D floorplans using statistical analysis by Gasiorowski, Pawel, Vassilev, Vassil

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A reformulation of additive models by Wozniakowski, Alex

“…Additive models and their fitting algorithms play a pivotal role in the history and development of applied mathematics, machine learning, statistics, and science. …”
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Modelling and characterization of membrane fouling in osmotically-driven membrane processes (ODMPs) by Lai, Li

“…From qualitive analysis to quantitative analysis, the location of peak raised by colloidal deposition is used to differentiate the deposition on surface of active layer and inside of support layer after being analyzed by arrival time shift and confirmed by statistical testing. Moreover, the further short-time Fourier transformation (STFT) was applied to transfer the original time domain data into time-frequency domain, which reveal a noticeable magnitude reduction on high frequency components when Rayleigh scattering was triggered by particle inside of membrane pores. …”
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Racial discrimination against prospective tenants : evidence from the room rental market in Singapore by Chew, Ilynn Mei Xian, Goh, Pei Ying, Ng, Wan Zhyi

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Hedonic regression model : influence of housing characteristics and housing lease on HDB's resale price by Ng, Darren Kaiwen, Nah, Hng Meng

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Combating China’s corruption through learning from Taobao’s business model. by Tan, Winifred Guan Xin., Soh, Rachel Mei Hui., Choo, Amelene Isabel.

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

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Fast and accurate detection of Identical-By-Descent segment sharing in large genomic datasets by Saada, J

Measuring magic on a quantum processor by Oliviero, Salvatore F. E., Leone, Lorenzo, Hamma, Alioscia, Lloyd, Seth

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Situasi Pembelajaran Bahasa Asing dalam Kalangan Pelajar di Universiti Utara Malaysia dalam Norma Baharu dengan Menggunakan Model UTAUT (S/O 14775) by Mansor, Masni, Abdul Hamid, Aida Husni, Sanguan, Soraya, Md Yusoff, Mohd Farid

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The intransitive dice kernel: $$\frac{\mathbbm {1}_{x\ge y}-\mathbbm {1}_{x\le y}}{4} - \frac{3(x-y)(1+xy)}{8}$$ by Sah, Ashwin, Sawhney, Mehtaab

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The application of prospect theory in travel choice behavioral analysis by Hariharan Subramaniam.

“…The most widely used and accepted model for predicting and analysing of travel behaviour would be the Utility Theory. …”
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Questionnaire data analysis using information geometry by Har-Shemesh, Omri, Quax, Rick, Lansing, J. Stephen, Sloot, Peter M. A.

“…The SM has deep connections with parametric statistical models and the theory of phase transitions in statistical physics. …”
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Uncertainty quantification framework for combined statistical spatial downscaling and temporal disaggregation for climate change impact studies on hydrology by Rajendran Queen Suraajini

“…The Statistical Downscaling Model (SDM) is the bridging model which is used to downscale the output from the General Circulation Model (GCM) for increasing the spatial resolution of future climate scenarios. …”
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Sentiment analysis and topic modelling of 2024 U.S. and Indonesian election tweets: a study of political discourse and public opinion by Widawati, Elisia Brispalma

“…This study investigates the effectiveness of various deep learning architectures and statistical models in both sentiment analysis and the temporal analysis of online public discourse through topic modelling and sentiment forecasting of tweets related to the 2024 Indonesian and U.S. elections. …”
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