Meta-analysis: Minimizing errors

Minimizing Errors in Electron Microprobe Analysis.

Errors in quantitative electron microprobe analysis arise from many sources including those associated with sampling, specimen preparation, instrument operation, data collection, and analysis. The relative magnitudes of some of these factors are assessed for a sample of NiAl used to demonstrate important concerns in the analysis of even a relatively simple system measured under standard operati...

Map Projections Minimizing Distance Errors

It is useful to have mathematical criteria for evaluating errors in map projections. The Chebyshev criterion for minimizing rms (root mean square) local scale factor errors for conformal maps has been useful in developing conformal map projections of continents. However, any local error criterion will be minimized ultimately by map projections with multiple interruptions. A disadvantage of inte...

Minimizing Binding Errors Using Learned

Minimizing Binding Errors Using Learned Conjunctive Features

We have studied some of the design trade-offs governing visual representations based on spatially invariant conjunctive feature detectors, with an emphasis on the susceptibility of such systems to false-positive recognition errors-Malsburg's classical binding problem. We begin by deriving an analytical model that makes explicit how recognition performance is affected by the number of objects th...

Errors of measurement for blood volume parameters: a meta-analysis.

The volume of red blood cells (V(RBC)) is used routinely in the diagnostic workup of polycythemia, in assessing the efficacy of erythropoietin administration, and to study factors affecting oxygen transport. However, errors of various methods of measurement of V(RBC) and related parameters are not well characterized. We meta-analyzed 346 estimates of error of measurement of V(RBC) for technique...