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  2. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    In Analytica release 4.4, the Smoothing option for PDF results uses KDE, and from expressions it is available via the built-in Pdf function. In C/C++, FIGTree is a library that can be used to compute kernel density estimates using normal kernels. MATLAB interface available. In C++, libagf is a library for variable kernel density estimation.

  3. Multivariate kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_kernel...

    Multivariate kernel density estimation. Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics. It can be viewed as a generalisation of histogram density estimation with improved statistical properties.

  4. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    A histogramis a visual representation of the distributionof quantitative data. To construct a histogram, the first step is to "bin" (or "bucket")the range of values— divide the entire range of values into a series of intervals—and then count how many values fall into each interval. The bins are usually specified as consecutive, non ...

  5. Cell cycle analysis - Wikipedia

    en.wikipedia.org/wiki/Cell_cycle_analysis

    Cell cycle analysis by DNA content measurement is a method that most frequently employs flow cytometry to distinguish cells in different phases of the cell cycle.Before analysis, the cells are usually permeabilised and treated with a fluorescent dye that stains DNA quantitatively, such as propidium iodide (PI) or 4,6-diamidino-2-phenylindole (DAPI).

  6. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    e. In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts ...

  7. Violin plot - Wikipedia

    en.wikipedia.org/wiki/Violin_plot

    Violin plots are similar to box plots, except that they also show the probability density of the data at different values, usually smoothed by a kernel density estimator.A violin plot will include all the data that is in a box plot: a marker for the median of the data; a box or marker indicating the interquartile range; and possibly all sample points, if the number of samples is not too high.

  8. Andrews plot - Wikipedia

    en.wikipedia.org/wiki/Andrews_plot

    An Andrews curve for the Iris data set. In data visualization, an Andrews plot or Andrews curve is a way to visualize structure in high-dimensional data. It is basically a rolled-down, non-integer version of the Kent–Kiviat radar m chart, or a smoothed version of a parallel coordinate plot.

  9. Split graph - Wikipedia

    en.wikipedia.org/wiki/Split_graph

    A split graph, partitioned into a clique and an independent set. In graph theory, a branch of mathematics, a split graph is a graph in which the vertices can be partitioned into a clique and an independent set. Split graphs were first studied by Földes and Hammer (1977a, 1977b), and independently introduced by Tyshkevich and Chernyak (1979 ...