Results 151 to 160 of about 8,300 (176)

Integrating preliminary test and Stein-type techniques to improve estimation in the time-dependent Cox model. [PDF]

PLoS One
Ramezani R, Rabiei MR, Arashi M.
europepmc   +1 more source

Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint T₁, T₂, and M₀ Mapping. [PDF]

J Magn Reson Imaging
Liu Z, Liu Z, Rashid I, Galizia MS, Scoma C, Truesdell W, Agarwal P, Seiberlich N, Shen L, Hamilton J.   +9 more
europepmc   +1 more source

When can neuronal activity-dependent homeostatic plasticity maintain circuit-level properties? [PDF]

J Comput Neurosci
Stolting LJ, Beer RD.
europepmc   +1 more source

Brain-wide arousal signals are segregated from movement planning in the superior colliculus of the macaque. [PDF]

Elife
Johnston R, Smith MA.
europepmc   +1 more source

Near-Field Source Localization in Nonuniform Noise: An Efficient Symmetric Matrix Factorization-Based Approach. [PDF]

Sensors (Basel)
Song W, He Z, Sun G, Feng S.
europepmc   +1 more source

Automatic Modal Parameter Identification for Offshore Wind Turbines Using Modified Clustering-Based Methodology. [PDF]

Sensors (Basel)
Yang Y, Liang F, Zhu Q, Zhang H.
europepmc   +1 more source

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Feature filter for estimating central mean subspace and its sparse solution

Computational Statistics & Data Analysis, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pei Wang, Xiangrong Yin, Qingcong Yuan, Richard J. Kryscio   +3 more
openaire   +3 more sources

Fused clustering mean estimation of central subspace

Journal of the Korean Statistical Society, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Um, Hye Yeon, Yoo, Jae Keun
openaire   +4 more sources

Central Mean Subspace in Time Series

Journal of Computational and Graphical Statistics, 2009
We propose a notion of central mean dimension reduction subspace for time series {xt} which does not require specification of a model but seeks to find a p×d matrix Φd, d≤p, so that the d×1 vector ΦdTXt−1, where Xt−1=(xt−1, …, xt−p)T for some p≥1, includes all the information about xt that is available from E(xt|Xt−1).
Jin-Hong Park, T. N. Sriram, Xiangrong Yin   +2 more
openaire   +3 more sources