Search Results - mathematical and statistical methods in the innovation process

Nutritional improvement process for Blue Cibacron bleaching by Coprinus cinereus strain through statistical mathematical methods by Channaoui, Sanaâ, Blaghen, Mohamed, Errachidi, Faouzi

“…The study of the Blue Cibacron treatment process through an statistical mathematical methods allows the authors to determine a relation between nutritional variables, which are nitrogen source…”
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Scientific discovery in a model-centric framework: Reproducibility, innovation, and epistemic diversity by Devezer, Berna, Nardin, Luis G., Baumgaertner, Bert, Buzbas, Erkan Ozge

“… We build a mathematical model of scientific discovery that presents a viable framework to study its desirable properties including reproducibility…”
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Succeeding in innovation: key insights on the role of R&D and technological acquisition drawn from company data by Conte, Andrea, Vivarelli, Marco

“…This paper discusses the relationship between a company’s investment in innovation and its success in introducing new product and/or process innovations…”
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Simultaneous inference and trend specification testing in ARMA model with trend via innovation distribution function by Zhong, Chen

“…The innovation distribution function in the ARMA model with trend is estimated by the kernel distribution estimator (KDE…”
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Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics by Ren, Zekun, Oviedo, Felipe, Thway, Maung, Tian, Siyu I. P., Wang, Yue, Xue, Hansong, Dario Perea, Jose, Layurova, Mariya, Heumueller, Thomas, Birgersson, Erik, Aberle, Armin G., Brabec, Christoph J., Stangl, Rolf, Li, Qianxiao, Sun, Shijing, Lin, Fen, Peters, Ian Marius, Buonassisi, Tonio

“…Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or…”
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Industrial Control Systems: Mathematical and Statistical Models and Techniques by Badiru, Adedeji B., Ibidapo-Obe, Oye, Ayeni, Babatunde J.

“…This book presents the mathematical foundation for building and implementing industrial control systems…”
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A Simple Asymptotically F-Distributed Portmanteau Test for Diagnostic Checking of Time Series Models With Uncorrelated Innovations by Wang, Xuexin, Sun, Yixiao

“…We propose a simple asymptotically F-distributed portmanteau test for diagnostically checking whether the innovations in a parametric time series model are uncorrelated while allowing them to exhibit…”
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Testing the existence of moments for GARCH processes by Francq, Christian, Zakoïan, Jean-Michel

“… on the distribution of the innovation, higher-order moment conditions involve moments of the independent innovation process…”
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Center-Outward R-Estimation for Semiparametric VARMA Models by Hallin, M., La Vecchia, D., Liu, H.

“…We propose a new class of R-estimators for semiparametric VARMA models in which the innovation density plays the role of the nuisance parameter…”
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Innovations in statistical modeling to connect data, chance and context by Pfannkuch, Maxine, Ben-Zvi, Dani, Budgett, Stephanie

“…Statistical modeling is emerging as a fertile research environment in which to promote and learn about student statistical reasoning processes…”
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Transformed regression-based long-horizon predictability tests by Demetrescu, Matei, Rodrigues, Paulo M.M., Taylor, A.M. Robert

“… Second, they are valid under much weaker conditions on the innovations than extant…”
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Statistical identification in panel structural vector autoregressive models based on independence criteria by Herwartz, Helmut, Wang, Shu

“… For identification, we impose independence of structural innovations at the pooled level. We demonstrate robustness of the method under cross…”
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Product market regulation and innovation efficiency by Franco, Chiara, Pieri, Fabio, Venturini, Francesco

“…We study the role of upstream product market regulation (PMR) in innovation efficiency…”
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A Robust Generalized-Maximum Likelihood Unscented Kalman Filter for Power System Dynamic State Estimation by Zhao, Junbo, Mili, Lamine

“…) that is able to suppress observation and innovation outliers while filtering out non-Gaussian process and measurement noise…”
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On the integrated mean squared error of wavelet density estimation for linear processes by Beknazaryan, Aleksandr, Sang, Hailin, Adamic, Peter

“… ). Under some regular conditions on the characteristic function of innovations, we achieve, based on the number of nonzero coefficients in the linear process, the minimax optimal convergence rate…”
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Local explosion modelling by non-causal process by Gourieroux, Christian, Zakoian, Jean-Michel

“…The non-causal auto-regressive process with heavy-tailed errors has non-linear causal dynamics, which allow for local explosion or asymmetric cycles that are often observed in economic and financial time series…”
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Testing for a Moderately Explosive Process with Structural Change in Drift by Xiang, Jingjie, Guo, Gangzheng, Zhao, Qing

“… explosiveness under different dependence structures. When the innovation sequence is independently and identically distributed (i.i.d…”
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Impacts of innovation school system in Korea: a latent space item response model with Neyman–Scott point process by Yi, Seorim, Kim, Minkyu, Park, Jaewoo, Jeon, Minjeong, Jin, Ick Hoon

“…’ creativity as well as their non-cognitive skills. To better understand the differences between innovation and regular school systems in South Korea, we propose a novel method that combines the latent space item response model with the Neyman…”
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Modeling of Retinal Optical Coherence Tomography Based on Stochastic Differential Equations: Application to Denoising by Tajmirriahi, Mahnoosh, Amini, Zahra, Hamidi, Arsham, Zam, Azhar, Rabbani, Hossein

“…), is proposed for retinal Optical Coherence Tomography (OCT) images. In this method, pixel intensities of image are considered as discrete realizations of a Levy stable process…”
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Identification of structural vector autoregressions through higher unconditional moments by Guay, Alain

“…This paper pursues two objectives. First, we determine the sufficient condition for local, statistical identification of SVAR processes through the third and fourth unconditional moments of the reduced-form innovations…”
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