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Instant-use add-on functions for the Wolfram Language
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Linear model fitting discarding outliers
ResourceFunction["TrimmedLinearFit"][data,basis,vars] finds a least-squares linear fit of basis to data when 5% of the outliers are discarded. | |
ResourceFunction["TrimmedLinearFit"][data,basis,vars, n] finds a least-squares linear fit of basis to data when n outliers are discarded. | |
ResourceFunction["TrimmedLinearFit"][data,basis,vars, Scaled[n]] finds a least-squares linear fit of basis to data when a proportion n of outliers are discarded. |
Find a fit ignoring a single outlier:
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Fit would be unduly influenced by the large outlier:
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In this case, TrimmedLinearFit is broadly equivalent to:
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The amount of trimming can be specified as a proportion of the data, for example, discarding 30% of the data:
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Data and models can be multidimensional:
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Wolfram Language 11.3 (March 2018) or above
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