Results 231 to 240 of about 1,640,518 (270)

Least Absolute Deviations Curve-Fitting

SIAM Journal on Scientific and Statistical Computing, 1980
A method is proposed for least absolute deviation curve fitting. It may be used to obtain least absolute deviations fits of general linear regressions. As a special case it includes a minor variant of a method for fitting straight lines by least absolute deviations that was previously thought to possess no generalization.
Bloomfield, Peter, Steiger, William
openaire   +2 more sources

Conditional median absolute deviation

Journal of Statistical Computation and Simulation, 2014
We introduce conditional median absolute deviation to characterize how the local variability of one quantitative random variable varies with another one. A two-step estimation procedure is proposed and the resultant estimator possesses an adaptiveness property. Simulation indicates that this estimator is much more efficient than its competitors such as
Tingyou Zhou, Liping Zhu
openaire   +1 more source

Minimizing Absolute Deviations

The American Statistician, 1964
the least-squares line for the above data is + .414, as usual slightly higher than the least-deviations line. This tendency for the least-deviations line to be slightly shallower is largely due to its lesser sensitivity to isolated or unusually high y-values. Where correlation is low, this tendency is not noticeable.
openaire   +1 more source

Least‐absolute‐deviations position finding

Naval Research Logistics Quarterly, 1982
AbstractPosition finding has historically been carried out by calculating the coordinates of the mean position via a least‐squares procedure based on the distance of the position from several direction lines. It has been suggested that the least‐squares procedure assigns too much weight to outliers among the set of direction lines, outliers which may ...
openaire   +1 more source

Alternatives to the Median Absolute Deviation

Journal of the American Statistical Association, 1993
Abstract In robust estimation one frequently needs an initial or auxiliary estimate of scale. For this one usually takes the median absolute deviation MAD n = 1.4826 med, {|xi − med j x j |}, because it has a simple explicit formula, needs little computation time, and is very robust as witnessed by its bounded influence function and its 50% breakdown ...
Rousseeuw, Peter, Croux, C.
openaire   +2 more sources

Edge preserving image enhancement using median absolute deviation and iterative median absolute deviation

2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), 2017
The aim of image enhancement is to produce a processed image which is more suitable than the original image for specific application. Application can be edge detection, boundary detection, image fusion, segmentation etc. In this paper different types of image enhancement algorithms in spatial domain are presented for gray scale images.
null Shivaprasad, Clitus D'Souza, P Vinay   +2 more
openaire   +1 more source

Least orthogonal absolute deviations

Computational Statistics & Data Analysis, 1988
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Least Absolute Deviation Cut

2011
The paper discussed a new additive extension of minimum cut by simultaneously minimizing intra cluster similarity bias and inter cluster similarity, Least Absolute Deviation Cut (LAD cut). The LAD cut can be proved convergent in finite iterative steps, and its theoretical conditions that the LAD cut can work well is also presented.
Jian Yu, Liping Jing
openaire   +1 more source

Permutation Tests for Least Absolute Deviation Regression

Biometrics, 1996
A permutation test based on proportionate reduction in sums of absolute deviations when passing from reduced to full parameter models is developed for testing hypotheses about least absolute deviation (LAD) estimates of conditional medians in linear regression models.
Cade, Brian S., Richards, Jon D.
openaire   +2 more sources

Minimizing the maximum absolute deviation

ACM SIGMAP Bulletin, 1976
In a recent educational technical note in SIGMAP, [3], Swanson and Woolsey outlined how one can determine the unknown parameters of a linear model under the criterion of minimizing the sum of absolute deviations. This note will demonstrate that one can also use linear programming procedures under the criterion of minimizing the maximum absolute ...
openaire   +1 more source