Results 271 to 280 of about 71,763 (309)

Stochastic semiparametric regression for spectrum cartography

2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015
An online spectrum cartography algorithm is proposed to reconstruct power spectral density (PSD) maps in space and frequency based on compressed and quantized sensor measurements. The emerging regression task is addressed by decomposing the PSD at every location into a linear combination of the power spectra (due to individual transmitters and ...
Daniel Romero 0004, Seung-Jun Kim 0002, Georgios B. Giannakis   +2 more
openaire   +1 more source

Preconditioned Bayesian Regression for Stochastic Chemical Kinetics

Journal of Scientific Computing, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alen Alexanderian, Francesco Rizzi, Muruhan Rathinam, Olivier P. Le Maître, Omar M. Knio   +4 more
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Stochastic algorithms in nonlinear regression

Computational Statistics & Data Analysis, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Křivý, I., Tvrdík, J., Krpec, R.
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A stochastic frontier regression model with dynamic frontier

Communications in Statistics - Simulation and Computation, 2020
We consider a stochastic frontier regression model with a time dependent efficiency process, which is assumed to follow an exponential autoregressive sequence.
T. V. Ramanathan, Neelabh Rohan, Bovas Abraham   +2 more
openaire   +1 more source

Stochastic covariates in binary regression

2004
Summary: Binary regression has many medical applications. In applying the technique, the tradition is to assume the risk factor \(X\) as a non-stochastic variable. In most situations, however, \(X\) is stochastic. In this study, we discuss the case when \(X\) is stochastic in nature, which is more realistic from a practical point of view than \(X ...
ORAL, Evrim, GÜNAY, Süleyman
openaire   +2 more sources

Stochastic approximation with a nonstationary regression function (Corresp.)

IEEE Transactions on Information Theory, 1972
This correspondence is concerned with a stochastic approximation algorithm having a nonstationary regression function. Convergence conditions and a mean-square error bound are presented. Its possible application to feedback communication is discussed briefly.
Tzay Y. Young, R. Westerberg
openaire   +1 more source

Broad stochastic configuration network for regression

Knowledge-Based Systems, 2022
Chenglong Zhang 0001, Shifei Ding, Wei Du 0010   +2 more
openaire   +1 more source

Stochastic Approximation and NonLinear Regression

2003
This monograph addresses the problem of "real-time" curve fitting in the presence of noise, from the computational and statistical viewpoints. It examines the problem of nonlinear regression, where observations are made on a time series whose mean-value function is known except for a vector parameter.
Arthur E. Albert, Leland A. Gardner
openaire   +1 more source

Stochastic Approximation and Nonlinear Regression

Technometrics, 1969
W. T. Federer, A. E Albert, L. A. Gardner   +2 more
openaire   +2 more sources

Stochastic DCA for Sparse Multiclass Logistic Regression

2017
In this paper, we deal with the multiclass logistic regression problem, one of the most popular supervised classification method. We aim at developing an efficient method to solve this problem for large-scale datasets, i.e. large number of features and large number of instances.
Hoai An Le Thi, Hoai Minh Le, Duy Nhat Phan, Bach Tran   +3 more
openaire   +1 more source