Results 301 to 310 of about 3,885,632 (340)
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DeepLabCut: markerless pose estimation of user-defined body parts with deep learning
Nature Neuroscience, 2018Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis can be
Alexander Mathis +6 more
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Estimation of Variance of the Regression Estimator
Journal of the American Statistical Association, 1987Abstract 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.
Chien-Fu Wu, Lih-Yuan Deng
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On the Estimation of Contrasts in Linear Estimation
Calcutta Statistical Association Bulletin, 1973This paper examines the conditions on the coefficient matrix of the linear model under which contrasts, and contrasts alone, are estimated by contrasts.
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Robust Estimation Through Estimating Equations
Biometrika, 1984The paper deals with the choice of parameter definition. It develops the concepts of parameter defining function and effective parameter. It also provides theory and techniques for choosing from a given set of robust parameters the one that can most efficiently be estimated. This theory is applied to location parameters.
M. E. Thompson, V. P. Godambe
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Journal of Mathematical Sciences, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Biometrika, 1988
A time series model of the form \[ X_ t=a\cos (wt+f)+e_ t \] where \(e_ t\) is a stationary noise sequence is considered. The paper discusses a least squares procedure for estimating a, w and f of the harmonic component. One aim of the paper is to see how reliable the asymptotic theory of the estimates of w is.
John Rice, Murray Rosenblatt
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A time series model of the form \[ X_ t=a\cos (wt+f)+e_ t \] where \(e_ t\) is a stationary noise sequence is considered. The paper discusses a least squares procedure for estimating a, w and f of the harmonic component. One aim of the paper is to see how reliable the asymptotic theory of the estimates of w is.
John Rice, Murray Rosenblatt
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A-posteriori estimation of the error in the error estimate
Computer Methods in Applied Mechanics and Engineering, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
D.K. Datta +4 more
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2007
This chapter describes the four main methods of estimating and their approximate levels of accuracy. These methods are: subjective (±20%–40%), parametric (±10%–20%), comparative (±10%) and analytical (±5%). The need to always allow a contingency is stressed and a diagram shows how the accuracy percentage improves as the project moves from the concept ...
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This chapter describes the four main methods of estimating and their approximate levels of accuracy. These methods are: subjective (±20%–40%), parametric (±10%–20%), comparative (±10%) and analytical (±5%). The need to always allow a contingency is stressed and a diagram shows how the accuracy percentage improves as the project moves from the concept ...
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2003
We know from our basic knowledge of statistics that one of the objectives in statistics is to better understand and model the underlying process which generates data. This is known as statistical inference: we infer from information contained in sample properties of the population from which the observations are taken.
Léopold Simar, Wolfgang Karl Härdle
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We know from our basic knowledge of statistics that one of the objectives in statistics is to better understand and model the underlying process which generates data. This is known as statistical inference: we infer from information contained in sample properties of the population from which the observations are taken.
Léopold Simar, Wolfgang Karl Härdle
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