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The first stage consists of a less known criterion for filtering spurious data (outliers).
Data outliers or other data inhomogeneities lead to a violation of the assumptions of traditional statistical estimators and methods.
Measurement noises and data outliers are the most common effects which lead to poor quality of process data.
In fact, finding data outliers that may be indicative of mineralization (in exploration geochemistry) or contamination (in environmental geochemistry) is one of the major aims of geochemical surveys29.
BRTs can deal with missing data, outliers, non-linearity, multicollinearity, irrelevant predictors, and violations of traditional statistical assumptions including independence of data and unequal variances29,32.
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According to federal data, outlier payments to Redding were off the charts.
Finally, for detection of the probable doubtful CO2 MMP data, outlier diagnosis was performed on the data sets.
For such input data, outlier detection based on the curvature of a point sequence may not work well.
Obviously more programming is needed for reading the data, outlier control, data transformation, and post-processing the results to calculate confidence intervals, equivalence limits and plotting the graphs.
For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com