Table of Contents
19 relations: Coefficient of variation, Cumulative distribution function, Hyperexponential distribution, Journal of Theoretical Biology, Lagrange polynomial, Laplace transform, Marcel F. Neuts, Markov chain, Matrix exponential, Molecular Biology and Evolution, Probability density function, Probability distribution, Probability theory, Queueing theory, Real number, Row and column vectors, Stochastic process, Teletraffic engineering, Vrije Universiteit Amsterdam.
Coefficient of variation
In probability theory and statistics, the coefficient of variation (CV), also known as normalized root-mean-square deviation (NRMSD), percent RMS, and relative standard deviation (RSD), is a standardized measure of dispersion of a probability distribution or frequency distribution.
See Hypoexponential distribution and Coefficient of variation
Cumulative distribution function
In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable X, or just distribution function of X, evaluated at x, is the probability that X will take a value less than or equal to x. Every probability distribution supported on the real numbers, discrete or "mixed" as well as continuous, is uniquely identified by a right-continuous monotone increasing function (a càdlàg function) F \colon \mathbb R \rightarrow satisfying \lim_F(x).
See Hypoexponential distribution and Cumulative distribution function
Hyperexponential distribution
In probability theory, a hyperexponential distribution is a continuous probability distribution whose probability density function of the random variable X is given by where each Yi is an exponentially distributed random variable with rate parameter λi, and pi is the probability that X will take on the form of the exponential distribution with rate λi. Hypoexponential distribution and hyperexponential distribution are continuous distributions.
See Hypoexponential distribution and Hyperexponential distribution
Journal of Theoretical Biology
The Journal of Theoretical Biology is a biweekly peer-reviewed scientific journal covering theoretical biology, as well as mathematical, computational, and statistical aspects of biology.
See Hypoexponential distribution and Journal of Theoretical Biology
Lagrange polynomial
In numerical analysis, the Lagrange interpolating polynomial is the unique polynomial of lowest degree that interpolates a given set of data.
See Hypoexponential distribution and Lagrange polynomial
Laplace transform
In mathematics, the Laplace transform, named after Pierre-Simon Laplace, is an integral transform that converts a function of a real variable (usually t, in the time domain) to a function of a complex variable s (in the complex-valued frequency domain, also known as s-domain, or s-plane).
See Hypoexponential distribution and Laplace transform
Marcel F. Neuts
Marcel Fernand Neuts (21 February 1935 – 9 March 2014) is a Belgian-American mathematician and probability theorist.
See Hypoexponential distribution and Marcel F. Neuts
Markov chain
A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event.
See Hypoexponential distribution and Markov chain
Matrix exponential
In mathematics, the matrix exponential is a matrix function on square matrices analogous to the ordinary exponential function.
See Hypoexponential distribution and Matrix exponential
Molecular Biology and Evolution
Molecular Biology and Evolution (MBE) is a monthly peer-reviewed scientific journal published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
See Hypoexponential distribution and Molecular Biology and Evolution
Probability density function
In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would be equal to that sample.
See Hypoexponential distribution and Probability density function
Probability distribution
In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment.
See Hypoexponential distribution and Probability distribution
Probability theory
Probability theory or probability calculus is the branch of mathematics concerned with probability.
See Hypoexponential distribution and Probability theory
Queueing theory
Queueing theory is the mathematical study of waiting lines, or queues.
See Hypoexponential distribution and Queueing theory
Real number
In mathematics, a real number is a number that can be used to measure a continuous one-dimensional quantity such as a distance, duration or temperature.
See Hypoexponential distribution and Real number
Row and column vectors
In linear algebra, a column vector with elements is an m \times 1 matrix consisting of a single column of entries, for example, \boldsymbol.
See Hypoexponential distribution and Row and column vectors
Stochastic process
In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a sequence of random variables in a probability space, where the index of the sequence often has the interpretation of time.
See Hypoexponential distribution and Stochastic process
Teletraffic engineering
Teletraffic engineering, telecommunications traffic engineering, or just traffic engineering when in context, is the application of transportation traffic engineering theory to telecommunications.
See Hypoexponential distribution and Teletraffic engineering
Vrije Universiteit Amsterdam
The (abbreviated as VU Amsterdam or simply VU when in context) is a public research university in Amsterdam, Netherlands, being founded in 1880.
See Hypoexponential distribution and Vrije Universiteit Amsterdam