Results 261 to 270 of about 71,763 (309)

A Machine Learning Framework for the Reconstruction of Composite Fatigue and Fracture Properties: A Synthetic Data Study. [PDF]

Materials (Basel)
Tiwari S, Gupta A.
europepmc   +1 more source

Methylation heterogeneity of the AQP1 promoter as a candidate prognostic biomarker in cholangiocarcinoma. [PDF]

Sci Rep
Yokoyama S, Noguchi H, Hamada T, Matsuo K, Akahane T, Kitazono I, Tasaki T, Murakami M, Ohtsuka T, Higashi M, Furukawa T, Tanimoto A.   +11 more
europepmc   +1 more source

Advancing Gastrointestinal Cancer Risk Prediction With Patient-Centered Machine Learning: Machine Learning Modeling Study. [PDF]

JMIR Med Inform
Baublyte D, Lee J, Gunathilake M, Kim J.
europepmc   +1 more source

Stochastic Regression Model with Dependent Disturbances [PDF]

Journal of Time Series Analysis, 2001
In this paper, we consider the estimation of the coefficient of a stochastic regression model whose explanatory variables and disturbances are permitted to exhibit short‐memory or long‐memory dependence. Three estimators of the coefficient are proposed.
Choy, Kokyo, Taniguchi, Masanobu
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Binary Regression with Stochastic Covariates

Communications in Statistics - Theory and Methods, 2006
In binary regression the risk factor X has been treated in the literature as a non-stochastic variable. In most situations, however, X is stochastic. We present solutions applicable to such situations. We show that our solutions are more precise than those obtained by treating X as non-stochastic when, in fact, it is stochastic.
exaly   +2 more sources

Heuristics for the regression of stochastic simulations

Journal of Simulation, 2013
Modelling and simulation environments that are stochastic in nature present a multitude of problems in the creation of meta-models, notably the reduction of the quality of fit due to statistical er...
Andrew James Turner, Santiago Balestrini-Robinson, Dimitri N. Mavris   +2 more
openaire   +1 more source

Switching regression metamodels in stochastic simulation

European Journal of Operational Research, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Isabel Reis dos Santos, Pedro M. Reis dos Santos   +1 more
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On the Averaged Stochastic Approximation for Linear Regression

SIAM Journal on Control and Optimization, 1996
Summary: For a linear regression function the average of stochastic approximation with constant gain is considered. In case of ergodic observations almost sure convergence is proved, where the limit is biased with small bias for small gain. For independent and identically distributed observations and also under martingale and mixing assumptions ...
Györfi, László, Walk, Harro
openaire   +2 more sources