Results 111 to 120 of about 103,329 (151)

The impact of online store specifications on enhancing the attractiveness of customer perception of the product: An analytical study of the opinions of a sample of Iraqi virtual store customers. [PDF]

F1000Res
Awni SA, Hammadi AA, Al-Halboosi IAM, Shakaterh HJM, Salman D, Ababneh AMNW, Stavytskyy A, Faleh Alazzam FA, Shakaterh RH.   +8 more
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Spatiotemporal characteristics and geophysical drivers of the fractal dimension and b-value in North China seismicity. [PDF]

PLoS One
Bi J, Li Y, Pan Y.
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Evaluation of Mindful Breathing Method Using Tablet Devices Through Chaos Analysis and Frequency Analysis: A Pilot Randomized Controlled Trial. [PDF]

Biomed Eng Comput Biol
Togo E.
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Skyrmions based on optical anisotropy for topological encoding. [PDF]

Light Sci Appl
Zhang Y, Wang AA, Zhang R, Zhao Z, Ma Y, Liu R, Pong ZK, Cai Y, He C.   +8 more
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Comparative analysis of stress wave propagation and rock damage evolution in water versus air medium decoupled blasting. [PDF]

Sci Rep
Peng J, Pan Y, Chen B, Han L, Xue F.
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Changes in the sagittal pharyngeal airway dimension following levelling and alignment in class II division 2 patients: a prospective clinical trial. [PDF]

Clin Oral Investig
Eid FY, Madian AM, Elfouly D.
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Sparse sufficient dimension reduction with heteroscedasticity

International Journal of Wavelets, Multiresolution and Information Processing, 2021
Heteroscedasticity often appears in the high-dimensional data analysis. In order to achieve a sparse dimension reduction direction for high-dimensional data with heteroscedasticity, we propose a new sparse sufficient dimension reduction method, called Lasso-PQR.
Haoyang Cheng, Wenquan Cui
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Sufficient Dimension Reduction and Graphics in Regression

Annals of the Institute of Statistical Mathematics, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
CHIAROMONTE, FRANCESCA, Cook RD
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Advance of the sufficient dimension reduction

WIREs Computational Statistics, 2020
AbstractThe sufficient dimension reduction of Li has been seen a steady development in the past 30 years in both methodology and application. The main approaches can be categorized into two groups: The inverse regression methods and forward regression methods.
Weiqiang Hang, Yingcun Xia
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