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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. XLfit can also analyse the statistical data.
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 ...
Line chart showing the population of the town of Pushkin, Saint Petersburg from 1800 to 2010, measured at various intervals. A line chart or line graph, also known as curve chart, [1] is a type of chart that displays information as a series of data points called 'markers' connected by straight line segments. [2]
Spreadsheet, Diagrams, Statistical Functions LiSiCA: Python: No 2015 Windows, Linux: Ligand-based virtual screening software that searches for 2D and 3D similarities between a reference compound and a database of target compounds. MagicPlot: GUI: Proprietary: No 2008: January 18, 2021 / 3.0: Any : Nonlinear fitting, batch processing Maple: GUI ...
Simfit – simulation, curve fitting, statistics, and plotting; SOCR; SOFA Statistics – desktop GUI program focused on ease of use, learn as you go, and beautiful output; Stan (software) – open-source package for obtaining Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo. It is somewhat like BUGS, but ...
The curves converge to a Dirac delta function peaked at u = 1 as β approaches 1, corresponding to the simple exponential function. Figure 2 . Linear and log-log plots of the stretched exponential distribution function G {\displaystyle G} vs t / τ {\displaystyle t/\tau }
The "moving average filter" is a trivial example of a Savitzky–Golay filter that is commonly used with time series data to smooth out short-term fluctuations and highlight longer-term trends or cycles. Each subset of the data set is fit with a straight horizontal line as opposed to a higher order polynomial.
In this example we try to fit the function = + using the Levenberg–Marquardt algorithm implemented in GNU Octave as the leasqr function. The graphs show progressively better fitting for the parameters a = 100 {\displaystyle a=100} , b = 102 {\displaystyle b=102} used in the initial curve.