When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. ggplot2 - Wikipedia

    en.wikipedia.org/wiki/Ggplot2

    ggplot2 is an open-source data visualization package for the statistical programming language R.Created by Hadley Wickham in 2005, ggplot2 is an implementation of Leland Wilkinson's Grammar of Graphics—a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers. ggplot2 can serve as a replacement for the base graphics in R and contains a ...

  3. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.

  4. V-optimal histograms - Wikipedia

    en.wikipedia.org/wiki/V-optimal_histograms

    A v-optimal histogram is based on the concept of minimizing a quantity which is called the weighted variance in this context. [1] This is defined as = =, where the histogram consists of J bins or buckets, n j is the number of items contained in the jth bin and where V j is the variance between the values associated with the items in the jth bin.

  5. Scott's rule - Wikipedia

    en.wikipedia.org/wiki/Scott's_Rule

    Scott's rule is a method to select the number of bins in a histogram. [1] Scott's rule is widely employed in data analysis software including R , [ 2 ] Python [ 3 ] and Microsoft Excel where it is the default bin selection method.

  6. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    Sturges's rule [1] is a method to choose the number of bins for a histogram.Given observations, Sturges's rule suggests using ^ = + ⁡ bins in the histogram. This rule is widely employed in data analysis software including Python [2] and R, where it is the default bin selection method.

  7. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    The top row is a series of plots using the escape time algorithm for 10000, 1000 and 100 maximum iterations per pixel respectively. The bottom row uses the same maximum iteration values but utilizes the histogram coloring method. Notice how little the coloring changes per different maximum iteration counts for the histogram coloring method plots.

  8. Density estimation - Wikipedia

    en.wikipedia.org/wiki/Density_Estimation

    In hydrology the histogram and estimated density function of rainfall and river discharge data, analysed with a probability distribution, are used to gain insight in their behaviour and frequency of occurrence. [9] An example is shown in the blue figure.

  9. Entropy estimation - Wikipedia

    en.wikipedia.org/wiki/Entropy_estimation

    with bin probabilities given by that histogram. The histogram is itself a maximum-likelihood (ML) estimate of the discretized frequency distribution [citation needed]), where is the width of the th bin. Histograms can be quick to calculate, and simple, so this approach has some attraction.