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On the Mean Absolute Error in Inverse Binomial Sampling
, 2009
"... A closedform expression and an upper bound are obtained for the mean absolute error of the unbiased estimator of a probability in inverse binomial sampling. The results given permit the estimation of an arbitrary probability with a prescribed level of the normalized mean absolute error. ..."
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A closedform expression and an upper bound are obtained for the mean absolute error of the unbiased estimator of a probability in inverse binomial sampling. The results given permit the estimation of an arbitrary probability with a prescribed level of the normalized mean absolute error.
On the use of Weighted Mean Absolute Error in Recommender Systems
"... The classical strategy to evaluate the performance of a Recommender System is to measure the error in rating predictions. But when focusing on a particular dimension in a recommending process it is reasonable to assume that every prediction should not be treated equally, its importance depends on th ..."
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on the degree to which the predicted item matches the deemed dimension or feature. In this paper we shall explore the use of weighted Mean Average Error (wMAE) as an alternative to capture and measure their effects on the recommendations. In order to illustrate our approach two different dimensions
Minimum Mean Absolute Error Stack Filtering with Structural Constraints and Goals
, 1990
"... Two approaches have been used in the past to design or choose a rankorder based filter to estimate a signal from a noisecorrupted observation of that signal: the structural approach and the estimation approach. In the structural approach, the goal is to find a filter which preserves those shapes ..."
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Cited by 24 (12 self)
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structural behavior. This theory of root signals for stack filters is then combined with the theory of minimum mean absolute error stack filtering. This new, unified theory allows the designer to pick a filter which minimizes noise subject to constraints on its structural behavior.
14A.7 VERIFICATION OF DETERMINISTIC TROPICAL CYCLONE INTENSITY FORECASTS: MOVING BEYOND MEAN ABSOLUTE ERROR
"... Deterministic forecasts of tropical cyclone (TC) intensity are typically verified by calculating a summary accuracy measure, such as mean absolute error or mean squared error. These summary mea ..."
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Deterministic forecasts of tropical cyclone (TC) intensity are typically verified by calculating a summary accuracy measure, such as mean absolute error or mean squared error. These summary mea
The Effect of Changing the Weighting of Errors in the Mean Absolute Error Criterion upon the Performance of Stack Filters
"... The present approach to the MAEbased design of stack filters for image restoration does not always produce results which are visually pleasing. We show that this problem can be corrected by performing the filtering in two stages, and by altering the weighting of errors in the mean absolute error cr ..."
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The present approach to the MAEbased design of stack filters for image restoration does not always produce results which are visually pleasing. We show that this problem can be corrected by performing the filtering in two stages, and by altering the weighting of errors in the mean absolute error
Closedform solution of absolute orientation using unit quaternions
 J. Opt. Soc. Am. A
, 1987
"... Finding the relationship between two coordinate systems using pairs of measurements of the coordinates of a number of points in both systems is a classic photogrammetric task. It finds applications in stereophotogrammetry and in robotics. I present here a closedform solution to the leastsquares pr ..."
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Cited by 989 (4 self)
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translational offset is the difference between the centroid of the coordinates in one system and the rotated and scaled centroid of the coordinates in the other system. The best scale is equal to the ratio of the rootmeansquare deviations of the coordinates in the two systems from their respective centroids
Representing twentieth century spacetime climate variability, part 1: development of a 196190 mean monthly terrestrial climatology
 Journal of Climate
, 1999
"... The construction of a 0.58 lat 3 0.58 long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wetday frequency, mean temperature, diurnal temperature range, vapor pressur ..."
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Cited by 581 (13 self)
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The construction of a 0.58 lat 3 0.58 long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wetday frequency, mean temperature, diurnal temperature range, vapor
Divergence measures based on the Shannon entropy
 IEEE Transactions on Information theory
, 1991
"... AbstractA new class of informationtheoretic divergence measures based on the Shannon entropy is introduced. Unlike the wellknown Kullback divergences, the new measures do not require the condition of absolute continuity to be satisfied by the probability distributions involved. More importantly, ..."
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Cited by 666 (0 self)
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AbstractA new class of informationtheoretic divergence measures based on the Shannon entropy is introduced. Unlike the wellknown Kullback divergences, the new measures do not require the condition of absolute continuity to be satisfied by the probability distributions involved. More importantly
RangeFree Localization Schemes for Large Scale Sensor Networks
, 2003
"... Wireless Sensor Networks have been proposed for a multitude of locationdependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of rangebased localization schemes that depend on absolute pointtopoint distance estimates. Because coarse accura ..."
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Cited by 525 (8 self)
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Wireless Sensor Networks have been proposed for a multitude of locationdependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of rangebased localization schemes that depend on absolute pointtopoint distance estimates. Because coarse
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