1985
DOI: 10.1016/0168-9002(85)90271-2
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Reconstruction of a strip geometry calorimeter using stepwise regression

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Cited by 11 publications
(4 citation statements)
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“…Here, the sensitive input data are sorted only by correlation coefficients, and for the selection this method may reject a predictor that is not very highly correlated but brings new information compared to other highly correlated predictors. So, before the selection of inputs, we use the stepwise regression method (Summers, 1985) to remove the highly correlated predictors which do not bring sufficient new information. In addition, we would like to make a cautionary note that correlation between climate input and the GRACE data does not necessarily represent causation, and in this case our (like any other similar) techniques may derive a “right answer due to the wrong reasons” but of course may fail in extrapolating well.…”
Section: Resultsmentioning
confidence: 99%
“…Here, the sensitive input data are sorted only by correlation coefficients, and for the selection this method may reject a predictor that is not very highly correlated but brings new information compared to other highly correlated predictors. So, before the selection of inputs, we use the stepwise regression method (Summers, 1985) to remove the highly correlated predictors which do not bring sufficient new information. In addition, we would like to make a cautionary note that correlation between climate input and the GRACE data does not necessarily represent causation, and in this case our (like any other similar) techniques may derive a “right answer due to the wrong reasons” but of course may fail in extrapolating well.…”
Section: Resultsmentioning
confidence: 99%
“…The second part generated a list of candidate particles with energy depositions which matched the sectors. For a detailed description of the calorimetry reconstruction program, refer to (31].…”
Section: Pass2mentioning
confidence: 99%
“…This position was then adjusted according to the known shower shapes. A stepwise regression fit [33] was used to merge the insignificant sectors into more significant ones. The transverse energy distribution of each sector was fit to a known electromagnetic shower shape plus a broader version of this shape used to approximate a hadronic shower.…”
Section: Slic and Hadrometer Reconstructionmentioning
confidence: 99%