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A mean squared error criterion for the design of experiments
Biometrika, 1983In estimating a response surface over a design region of interest, mean squared error can arise both from sampling variance and bias introduced by model inadequacy. The criterion adopted here for experimental design attempts to protect against bias resulting from a large class of deviations from the assumed model.
W. Welch
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On the mean squared error, the mean absolute error and the like
Communications in Statistics - Theory and Methods, 1999The problem of finding the minimizer of the rth -mean error , is revisited, via a unified approach. The approach is discussed for arbitrary r and is illustrated for r = 1 (mean absolute error)r = 2 (mean squared error), and r = 4. This approach is also discussed in the context of maximum likelihood estimation in a class of symmetric distributions which
Peter Enis +2 more
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Exact mean and mean squared error of the smoothed bootstrap mean integrated squared error estimator
Computational Statistics, 2000New expressions are obtained for the mean and mean squared error of the smoothed bootstrap mean integrated squared error estimator in Gaussian kernel estimation of normal mixture densities. The use of such densities is in the same spirit as Marron and Wand (1992) and provides the same benefits.
Dominic S. Lee, Carey E. Priebe
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2020
This chapter treats the problem of approximating and estimating the mean squared error of empirical best linear unbiased predictors of small area linear parameters under linear mixed models. This is done in several steps. First, when all the model parameters are unknown. Second, when only the variance component parameters are unknown.
Domingo Morales +3 more
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This chapter treats the problem of approximating and estimating the mean squared error of empirical best linear unbiased predictors of small area linear parameters under linear mixed models. This is done in several steps. First, when all the model parameters are unknown. Second, when only the variance component parameters are unknown.
Domingo Morales +3 more
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Number of Source Signal Estimation by the Mean Squared Eigenvalue Error
IEEE Transactions on Signal Processing, 2018Detection of the number of source signals (NoSS) in the presence of additive noise is considered. We present a new approach denoted by the mean squared eigenvalue error (MSEE). The MSEE is the mean squared error between the desired noise-free eigenvalues
S. Beheshti, S. Sedghizadeh
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Journal of machine learning research, 2014
We study a simple linear regression problem for grouped variables; we are interested in methods which jointly perform estimation and variable selection, that is, that automatically set to zero groups of variables in the regression vector. The Group Lasso
A. Aravkin +3 more
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We study a simple linear regression problem for grouped variables; we are interested in methods which jointly perform estimation and variable selection, that is, that automatically set to zero groups of variables in the regression vector. The Group Lasso
A. Aravkin +3 more
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On prediction and mean squared error
Canadian Journal of Statistics, 1992AbstractPractical questions motivate the search for predictors either of an as yet unobserved random vector, or of a random function of a parameter. An extension of the classical UMVUE theory is presented to cover such situations. In includes a Rao‐Blackwell‐type theorem, a Cramer‐Rao‐type inequality, and necessary and sufficient conditions for a ...
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MEAN SQUARE ERRORS OF POINT DETERMINATIONS
Empire Survey Review, 1944AbstractSome aspects of the problems attempted below have been discussed by many writers in the survey journals of Britain, Germany, Holland and other countries. Much of what is set down in the following pages is not new. Some of the curves and formulae have been re-discovered by the author and, although not original, they have been included so as to ...
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Minimum mean squared error equalization using a priori information
IEEE Transactions on Signal Processing, 2002A number of important advances have been made in the area of joint equalization and decoding of data transmitted over intersymbol interference (ISI) channels.
M. Tüchler, A. Singer, R. Koetter
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Truncated squarer with minimum mean-square error
Microelectronics Journal, 2014Abstract Squaring is an important arithmetic operation required in a multitude of applications. In this paper we present a truncated squarer that, with an n-bit input, produces its output on a number of bits that can be defined at design time in the [n,2n] range.
PETRA, NICOLA +4 more
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