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  2. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...

  3. Visual Basic for Applications - Wikipedia

    en.wikipedia.org/wiki/Visual_Basic_for_Applications

    As an example, VBA code written in Microsoft Access can establish references to the Excel, Word and Outlook libraries; this allows creating an application that – for instance – runs a query in Access, exports the results to Excel and analyzes them, and then formats the output as tables in a Word document or sends them as an Outlook email.

  4. List of spreadsheet software - Wikipedia

    en.wikipedia.org/wiki/List_of_spreadsheet_software

    It supports multiple tabs, VBA macro and PDF converting. [10] Lotus SmartSuite Lotus 123 – for MS Windows. In its MS-DOS (character cell) version, widely considered to be responsible for the explosion of popularity of spreadsheets during the 80s and early 90s. [citation needed] Microsoft Office Excel – for MS Windows and Apple Macintosh ...

  5. XLfit - Wikipedia

    en.wikipedia.org/wiki/XLfit

    XLfit is a Microsoft Excel add-in that can perform regression analysis, curve fitting, and statistical analysis. It is approved by the UK National Physical Laboratory and the US National Institute of Standards and Technology [ 1 ] XLfit can generate 2D and 3D graphs and analyze data sets.

  6. Non-linear least squares - Wikipedia

    en.wikipedia.org/wiki/Non-linear_least_squares

    Consider a set of data points, (,), (,), …, (,), and a curve (model function) ^ = (,), that in addition to the variable also depends on parameters, = (,, …,), with . It is desired to find the vector of parameters such that the curve fits best the given data in the least squares sense, that is, the sum of squares = = is minimized, where the residuals (in-sample prediction errors) r i are ...

  7. Spline interpolation - Wikipedia

    en.wikipedia.org/wiki/Spline_interpolation

    In addition to the three main conditions above, a clamped cubic spline has the conditions that ′ = ′ and ′ = ′ where ′ is the derivative of the interpolated function. In addition to the three main conditions above, a not-a-knot spline has the conditions that ‴ = ‴ and ‴ = ‴ ().

  8. Lagrange polynomial - Wikipedia

    en.wikipedia.org/wiki/Lagrange_polynomial

    Each Lagrange basis polynomial () can be rewritten as the product of three parts, a function () = common to every basis polynomial, a node-specific constant = (called the barycentric weight), and a part representing the displacement from to : [4]

  9. Akima spline - Wikipedia

    en.wikipedia.org/wiki/Akima_spline

    In applied mathematics, an Akima spline is a type of non-smoothing spline that gives good fits to curves where the second derivative is rapidly varying. [1] The Akima spline was published by Hiroshi Akima in 1970 from Akima's pursuit of a cubic spline curve that would appear more natural and smooth, akin to an intuitively hand-drawn curve.