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  2. Cell Transmission Model - Wikipedia

    en.wikipedia.org/wiki/Cell_Transmission_Model

    Since the original Cell Transmission model is a first order approximation, Daganzo [9] proposed the Lagged Cell Transmission Model (LCTM) that is more accurate than the former. This enhanced model uses lagged downstream density (p time steps earlier than the current time) for the receiving function.

  3. Weighted sum model - Wikipedia

    en.wikipedia.org/wiki/Weighted_Sum_Model

    In decision theory, the weighted sum model (WSM), [1] [2] also called weighted linear combination (WLC) [3] or simple additive weighting (SAW), [4] is the best known and simplest multi-criteria decision analysis (MCDA) / multi-criteria decision making method for evaluating a number of alternatives in terms of a number of decision criteria.

  4. Cell-based models - Wikipedia

    en.wikipedia.org/wiki/Cell-based_models

    Cell-based models are mathematical models that represent biological cells as discrete entities. Within the field of computational biology they are often simply called agent-based models [1] of which they are a specific application and they are used for simulating the biomechanics of multicellular structures such as tissues. to study the influence of these behaviors on how tissues are organised ...

  5. Spreadsheet - Wikipedia

    en.wikipedia.org/wiki/Spreadsheet

    A cell on a different sheet of the same spreadsheet is usually addressed as: =SHEET2!A1 (that is; the first cell in sheet 2 of the same spreadsheet). Some spreadsheet implementations in Excel allow cell references to another spreadsheet (not the currently open and active file) on the same computer or a local network.

  6. Explained sum of squares - Wikipedia

    en.wikipedia.org/wiki/Explained_sum_of_squares

    The general regression model with n observations and k explanators, the first of which is a constant unit vector whose coefficient is the regression intercept, is = + where y is an n × 1 vector of dependent variable observations, each column of the n × k matrix X is a vector of observations on one of the k explanators, is a k × 1 vector of true coefficients, and e is an n × 1 vector of the ...

  7. Kahan summation algorithm - Wikipedia

    en.wikipedia.org/wiki/Kahan_summation_algorithm

    The algorithm performs summation with two accumulators: sum holds the sum, and c accumulates the parts not assimilated into sum, to nudge the low-order part of sum the next time around. Thus the summation proceeds with "guard digits" in c , which is better than not having any, but is not as good as performing the calculations with double the ...

  8. 10,000 Steps Is A Myth. Here's What Science Says You Should ...

    www.aol.com/10-000-steps-myth-heres-110000541.html

    Step counting had long been used to measure distance—the word “mile” comes from the Latin milia passuum, or “one thousand paces,” and it’s said da Vinci thought his device could help ...

  9. Estimation of covariance matrices - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_covariance...

    Clearly, the difference between the unbiased estimator and the maximum likelihood estimator diminishes for large n. In the general case, the unbiased estimate of the covariance matrix provides an acceptable estimate when the data vectors in the observed data set are all complete: that is they contain no missing elements .