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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. Local regression - Wikipedia

    en.wikipedia.org/wiki/Local_regression

    Local regression or local polynomial regression, [1] also known as moving regression, [2] is a generalization of the moving average and polynomial regression. [3] Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced / ˈ l oʊ ɛ s / LOH-ess.

  4. Full width at half maximum - Wikipedia

    en.wikipedia.org/wiki/Full_width_at_half_maximum

    In other words, it is the width of a spectrum curve measured between those points on the y-axis which are half the maximum amplitude. Half width at half maximum (HWHM) is half of the FWHM if the function is symmetric. The term full duration at half maximum (FDHM) is preferred when the independent variable is time.

  5. Smoothing - Wikipedia

    en.wikipedia.org/wiki/Smoothing

    Smoothing may be distinguished from the related and partially overlapping concept of curve fitting in the following ways: . curve fitting often involves the use of an explicit function form for the result, whereas the immediate results from smoothing are the "smoothed" values with no later use made of a functional form if there is one;

  6. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    The points inside a curve labelled S represent elements of the set S, while points outside the boundary represent elements not in the set S. This lends itself to intuitive visualizations; for example, the set of all elements that are members of both sets S and T , denoted S ∩ T and read "the intersection of S and T ", is represented visually ...

  7. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    Inverted logistic S-curve to model the relation between wheat yield and soil salinity. Many natural processes, such as those of complex system learning curves, exhibit a progression from small beginnings that accelerates and approaches a climax over time. When a specific mathematical model is lacking, a sigmoid function is often used.

  8. Rankine's method - Wikipedia

    en.wikipedia.org/wiki/Rankine's_method

    Rankine's method or tangential angle method is an angular technique for laying out circular curves by a combination of chaining and angles at circumference, fully exploiting the theodolite and making a substantial improvement in accuracy and productivity over existing methods. This method requires access to only one road/path of communication ...

  9. Bathtub curve - Wikipedia

    en.wikipedia.org/wiki/Bathtub_curve

    The bathtub curve is a particular shape of a failure rate graph. This graph is used in reliability engineering and deterioration modeling. The 'bathtub' refers to the shape of a line that curves up at both ends, similar in shape to a bathtub. The bathtub curve has 3 regions: The first region has a decreasing failure rate due to early failures.