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Expectation–maximization algorithm. In statistics, an expectation–maximization ( EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. [1] The EM iteration alternates between performing an ...
The idea of the Arnoldi iteration as an eigenvalue algorithm is to compute the eigenvalues in the Krylov subspace. The eigenvalues of Hn are called the Ritz eigenvalues. Since Hn is a Hessenberg matrix of modest size, its eigenvalues can be computed efficiently, for instance with the QR algorithm, or somewhat related, Francis' algorithm.
The input–process–output model. The input–process–output (IPO) model, or input-process-output pattern, is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or other process. Many introductory programming and systems analysis texts introduce this as the ...
For example, most implementations of the C programming language do not perform array bounds checking. One can then exploit the implementation of the programming language by the compiler and the computer architecture's assembly language conventions, to achieve aliasing effects by writing outside of the array (a type of buffer overflow ).
Booth's multiplication algorithm is a multiplication algorithm that multiplies two signed binary numbers in two's complement notation. The algorithm was invented by Andrew Donald Booth in 1950 while doing research on crystallography at Birkbeck College in Bloomsbury, London. [1] Booth's algorithm is of interest in the study of computer ...
Concurrent computing. Concurrent computing is a form of computing in which several computations are executed concurrently —during overlapping time periods—instead of sequentially— with one completing before the next starts. This is a property of a system—whether a program, computer, or a network —where there is a separate execution ...
The simple Bonferroni correction rejects only null hypotheses with p-value less than or equal to , in order to ensure that the FWER, i.e., the risk of rejecting one or more true null hypotheses (i.e., of committing one or more type I errors) is at most . The cost of this protection against type I errors is an increased risk of failing to reject ...
Markovian arrival process. In queueing theory, a discipline within the mathematical theory of probability, a Markovian arrival process ( MAP or MArP [1]) is a mathematical model for the time between job arrivals to a system. The simplest such process is a Poisson process where the time between each arrival is exponentially distributed.