• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.247-254
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• 2004

Tusher, Tibshirani and Chu (2001) suggested SAM (Significance Analysis of Microarrays) to compare two groups under different conditions for each gene, using microarray data. They used two sample t-statistic adding fudge factor in the denominator to prevent the value of statistic from being inflated by large sample variance, which might result in significant difference despite of a small value in the numerator. This paper aims at finding robust fudge factor and replacing it in two-sample t-statistic used in SAM, which we call Modified SAM (MSAM). Using the simulated data and data used in Dudoit et al.(2002), it is shown that MSAM find significant genes better and has less error rate than SAM.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.208-216
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• 2020

Recently, issues regarding underground safety such as sink hole, ground subsidence and damage to old underground facilities have been increasing in urban areas, raising the need for more accurate management of underground facilities. Thus, this study derived a technique for comparing spatial data of underground facilities acquired from GPR exploration results acquired at the site with spatial data of integrated underground spatial maps. Using this underground space integrated map-linked service prototype program developed through this study, comparing the location information of the GPR exploration results and the underground space integrated map for the verification of site usability in some sections around Gangnam Station, the results demonstrated that the location of the map is 0.879m maximum, minimum of 0.101m and the average fudge factor was 0.625m. If accuracy of the GPR exploration results is guaranteed, it is judged that it can be used to improve the location accuracy of the underground space integration map.