'M-estimate' can also refer to...



New age estimates of M31 globular clusters from multicolour photometry

Estimating the catching efficiency of a 2-m beam trawl for sampling epifauna by removal experiments

Reproductive Biology and Mating System Estimates of Two Andean Melocacti, Melocactus schatzlii and M. andinus (Cactaceae)

Distance estimate and progenitor characteristics of SN 2005cs in M51

O-013A new nomogram for estimating 12-weeks survival in patients (pts) with chemorefractory metastatic colorectal cancer (mCRC)

A comparison of bedside renal function estimates and measured glomerular filtration rate (Tc99mDTPA clearance) in cancer patients

The method for consecutive subtraction of selected anomalies: the estimated crustal velocity structure in the 1996 Onikobe (M = 5.9) earthquake area, northeastern Japan

The sperm protamine mRNA ratio as a clinical parameter to estimate the fertilizing potential of men taking part in an ART programme

Application of the Analysis of Serum Antibodies (Immunoglobulins M and G) to Estimate the Seroprevalence of Ovine Oestrosis and to Evaluate the Effect of Chemotherapy

Describing the evolution of mobile technology usage for Latino patients and comparing findings to national mHealth estimates

Bayesian search for low-mass planets around nearby M dwarfs – estimates for occurrence rate based on global detectability statistics

Glomerular filtration rate estimated from the uptake phase of 99mTc-DTPA renography in chronic renal failure.

494 Low hematocrite seems to correlate with impaired left ventricular relaxation, estimated by color M-mode flow propagation, in patients with heart failure

Reply to the letter “Limitations of bedside estimates of renal function”, by M. J. Dooley and S. G. Poole (doi:10.1093/annonc/mdi173)

Perloff, Jeffrey M., Larry S. Karp, and Amos Golan, Editors. Estimating Market Power and Strategies. Cambridge,UK: Cambridge University Press, 2007, 352 pp., $88.99

User‐friendly algorithms for estimating completeness and diversity in randomized protein‐encoding libraries Wayne M. Patrick and Andrew E. Firth contributed equally to this work.

Deep 15 [math]m AKARI Observations in the CDFS: Estimating Dust Luminosities for a MIR-Selected Sample and for Lyman Break Galaxies and the Evolution of L dust L UV with the Redshift


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M-estimates are measures of location that are not as sensitive as the mean to outlier values. With observations x1, x2,…, xn, the sample mean can be characterized as the value of θ that minimizes , where g(u)=u2. The sample median can be characterized in a similar way, though now g(u)=|u|.

M-estimates can be characterized in this same way, but the functional forms for g are chosen to be less sensitive to outlier values. One frequently used alternative as a measure of location is the Huber function: where k is a tuning constant (often set equal to twice the median absolute deviation).

A second alternative is the biweight function: where k is again a tuning constant and is here often set equal to seven times the median absolute deviation. See also L-estimate.

Subjects: Probability and Statistics.

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