TY - JOUR
T1 - Estimation of regression parameters with arbitrary noise
AU - Goldenshluger, Alexander
PY - 1993/1
Y1 - 1993/1
N2 - The problem of estimation of linear regression parameters with arbitrary (nonzero mean, correlated and even nonrandom) noise is considered. The essential assumption is that the inputs are random, centered and independent of the noise. Convergence and rates of convergence for stochastic approximation (standard and with averaging) and least squares estimators are investigated under these conditions. Applications and generalizations of the obtained results are discussed.
AB - The problem of estimation of linear regression parameters with arbitrary (nonzero mean, correlated and even nonrandom) noise is considered. The essential assumption is that the inputs are random, centered and independent of the noise. Convergence and rates of convergence for stochastic approximation (standard and with averaging) and least squares estimators are investigated under these conditions. Applications and generalizations of the obtained results are discussed.
UR - https://www.researchgate.net/publication/265540576_Estimation_of_regression_parameters_with_arbitrary_noise
M3 - Article
SN - 1066-5307
VL - 2
SP - 18
EP - 29
JO - Mathematical Methods of Statistics
JF - Mathematical Methods of Statistics
ER -