Results 211 to 220 of about 71,521 (260)

Estimating Mixtures of Regressions

Journal of Computational and Graphical Statistics, 2003
This article shows how Bayesian inference for switching regression models and their generalizations can be achieved by the specification of loss functions which overcome the label switching problem common to all mixture models. We also derive an extension to models where the number of components in the mixture is unknown, based on the birthand-death ...
Hurn, Merrilee, Justel, Ana, Robert, Christian P.   +2 more
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An Improved Estimator of the Variance of the Regression Estimator

Biometrical Journal, 1999
Summary: The problem of estimation of variance of the general linear regression estimator has been considered. It has been shown that the first order calibration approach is a special case of the class of estimators proposed by \textit{L.-Y. Deng} and \textit{C. F. J. Wu} [J. Am. Stat. Assoc. 82, 568-576 (1987; Zbl 0629.62016)].
Singh, Sarjinder, Horn, Stephen
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On Estimating Regression

Theory of Probability & Its Applications, 1964
A study is made of certain properties of an approximation to the regression line on the basis of sampling data when the sample size increases unboundedly.
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Estimation of Multivariate Regression

Theory of Probability & Its Applications, 2004
Summary: Let \((X,Y)\) be a random vector whose first component takes values in a measurable space \(({\mathfrak{X}},{\mathfrak{A}},\mu)\) with measure \(\mu\), and let \(Y\) be a real-valued random variable. Let \(f(x)={\mathbf E}\{Y\mid X=x\} \) be the regression function of \(Y\) on \(X\).
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A robust Liu regression estimator

Communications in Statistics - Simulation and Computation, 2017
The least-squares regression estimator can be very sensitive in the presence of multicollinearity and outliers in the data. We introduce a new robust estimator based on the MM estimator.
Peter Filzmoser, Fatma Sevinç Kurnaz
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A Quick Estimate of the Regression Coefficient

Biometrika, 1958
1. In this note we investigate some properties of a 'quick' estimator, b', of the regression coefficient /? of a variable y on a variable x. This estimate has the advantage over the least squares estimate that (a) it is applicable to certain types of censored data, and (b) it provides a consistent estimator (under certain restrictions) of the slope ...
Barton, D. E., Casley, D. J.
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ESTIMATION AND INFERENCE IN PREDICTIVE REGRESSIONS [PDF]

Hitotsubashi Journal of Economics, 2011
This paper proposes new point estimates for predictive regressions. Our estimates are easily obtained by the least squares and the instrumental variable methods. Our estimates, called the plug-in estimates, have nice asymptotic properties such as median unbiasedness and the approximated normality of the associated t-statistics. In addition, the plug-in
KUROZUMI, EIJI, AONO, KOHEI
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Estimating Equivalence with Quantile Regression

Ecological Applications, 2010
Equivalence testing and corresponding confidence interval estimates are used to provide more enlightened statistical statements about parameter estimates by relating them to intervals of effect sizes deemed to be of scientific or practical importance rather than just to an effect size of zero.
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Estimation of Variance of the Regression Estimator

Journal of the American Statistical Association, 1987
Abstract The regression estimator and the ratio estimator are commonly used in survey practice. In the past more attention has been given to the ratio estimator because of its computational ease and applicability for general sampling designs. The ratio estimator is appropriate for populations whose regression line passes close to the origin.
Lih-Yuan Deng, C. F. J. Wu
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Variance estimation of survey estimates calibrated on estimated control totals—An application to the extended regression estimator and the regression composite estimator

Computational Statistics & Data Analysis, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yves G. Berger, Juan Francisco Muñoz, Eric Rancourt   +2 more
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