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  2. Nullity (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Nullity_(graph_theory)

    The nullity of a graph in the mathematical subject of graph theory can mean either of two unrelated numbers. If the graph has n vertices and m edges, then: In the matrix theory of graphs, the nullity of the graph is the nullity of the adjacency matrix A of the graph. The nullity of A is given by n − r where r is the rank of the adjacency

  3. Null model - Wikipedia

    en.wikipedia.org/wiki/Null_model

    One null model of utility in the study of complex networks is that proposed by Newman and Girvan, consisting of a randomized version of an original graph , produced through edges being rewired at random, under the constraint that the expected degree of each vertex matches the degree of the vertex in the original graph.

  4. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The nullity of a matrix is the dimension of the null space, and is equal to the number of columns in the reduced row echelon form that do not have pivots. [7] The rank and nullity of a matrix A with n columns are related by the equation:

  5. Null distribution - Wikipedia

    en.wikipedia.org/wiki/Null_distribution

    Null distribution is a tool scientists often use when conducting experiments. The null distribution is the distribution of two sets of data under a null hypothesis. If the results of the two sets of data are not outside the parameters of the expected results, then the null hypothesis is said to be true. Null and alternative distribution

  6. Design matrix - Wikipedia

    en.wikipedia.org/wiki/Design_matrix

    The design matrix has dimension n-by-p, where n is the number of samples observed, and p is the number of variables measured in all samples. [4] [5]In this representation different rows typically represent different repetitions of an experiment, while columns represent different types of data (say, the results from particular probes).

  7. Statistical classification - Wikipedia

    en.wikipedia.org/wiki/Statistical_classification

    The best class is normally then selected as the one with the highest probability. However, such an algorithm has numerous advantages over non-probabilistic classifiers: It can output a confidence value associated with its choice (in general, a classifier that can do this is known as a confidence-weighted classifier ).

  8. Fisher's exact test - Wikipedia

    en.wikipedia.org/wiki/Fisher's_exact_test

    It is one of a class of exact tests, so called because the significance of the deviation from a null hypothesis (e.g., p-value) can be calculated exactly, rather than relying on an approximation that becomes exact in the limit as the sample size grows to infinity, as with many statistical tests.

  9. Dataframe - Wikipedia

    en.wikipedia.org/wiki/Dataframe

    Data frames in the R programming language; Frame (networking) This page was last edited on 15 April 2023, at 18:29 (UTC). Text is available under the Creative ...