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Creators/Authors contains: "Kostinski, Sarah"

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  1. ; ; (, Physics Letters A)
    Linear least squares (LLS) is perhaps the most common method of data analysis, dating back to Legendre, Gauss and Laplace. Framed as linear regression, LLS is also a backbone of mathematical statistics. Here we report on an unexpected new connection between LLS and random walks. To that end, we introduce the notion of a random walk based on a discrete sequence of data samples (data walk). We show that the slope of a straight line which annuls the net area under a residual data walk equals the one found by LLS. For equidistant data samples this result is exact and holds for an arbitrary distribution of steps. 
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    Free, publicly-accessible full text available June 1, 2026
  2. ; ; (, The Journal of Physical Chemistry B)
    Full Text Available