Examples of using Distribution function in English and their translations into Turkish
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Given our distribution function, there is a maxima corresponding to R 0.
This follows from the inverse cumulative distribution function given above.
The Boltzmann equation for the distribution function of a gas in non-equilibrium states is still the most effective equation for studying transport phenomena in gases and metals.
Also, the force acting on the particles depends directly on the velocity distribution function ƒ.
In statistics, the Q-function is the tail distribution function of the standard normal distribution. .
Gas in a box- derivation of distribution functions for all ideal gases Bose gas Fermi gas Planck's law of black-body radiation- the distribution of photon energies as a function of frequency or wavelength Stefan-Boltzmann law- the total flux emitted by a black body Radiation pressure Baierlein, Ralph April 2001.
To assess prospective wind power sites a probability distribution function is often fit to the observed wind speed data.
The merit of theseequations is that the higher distribution functions f s+ 2, f s+ 3,…{\displaystyle f_{s+2}, f_{s+3},\dots} affect the time evolution of f s{\displaystyle f_{s}} only implicitly via f s+ 1.{\displaystyle f_{s+1}.} Truncation of the BBGKY chain is a common starting point for many applications of kinetic theory that can be used for derivation of classical or quantum kinetic equations.
James Jeans discovers that the dynamical constants of motion determine the distribution function for a system of particles.
The equation for an s-particle distribution function(probability density function) in the BBGKY hierarchy includes the(s+ 1)-particle distribution function thus forming a coupled chain of equations.
Note that although this model is termed a"Gaussian chain", the distribution function is not a gaussian(normal) distribution. .
In a parametric model, the probability distribution function has variable parameters, such as the mean and variance in a normal distribution, or the coefficients for the various exponents of the independent variable in linear regression.
Card(X) is also written X,♯X or|X|. cas- cos+ sin function. cdf-cumulative distribution function. c. f.- cumulative frequency. char- characteristic of a ring.
Model selection is a statistical method for selecting a distribution function within a class of them; e.g., in linear regression where the dependent variable is a polynomial of the independent variable with parametric coefficients, model selection is selecting the highest exponent, and may be done with nonparametric means, such as with cross validation.
Ludwig Boltzmann states the Boltzmann equation for the temporal development of distribution functions in phase space, and publishes his H-theorem.
The Kolmogorov-Smirnov test is based on cumulative distribution functions and can be used to test to see whether two empirical distributions are different or whether an empirical distribution is different from an ideal distribution. .
A distribution has a density function if and only if its cumulative distribution function F(x) is absolutely continuous.
Given this property, the lifetime distribution function and event density(F and f below) are well-defined.
The same integral with finite limitsis closely related to both the error function and the cumulative distribution function of the normal distribution. .
The end-to-end distance probability distribution function of a Gaussian chain is non-zero only for r> 0.
In most cases the electrons are close enough to thermal equilibrium that their temperature is relatively well-defined; this is true even when thereis a significant deviation from a Maxwellian energy distribution function, for example, due to UV radiation, energetic particles, or strong electric fields.
It is conventional to use a capital"F" for a cumulative distribution function, in contrast to the lower-case"f" used for probability density functions and probability mass functions.
A sum of discrete random variables is still a discrete random variable, so that we are confronted with a sequence ofdiscrete random variables whose cumulative probability distribution function converges towards a cumulative probability distribution function corresponding to a continuous variable namely that of the normal distribution. .
Such a probability distribution can alwaysbe captured by its cumulative distribution function F X( x) P( X≤ x){\displaystyle F_{ X}( x)=\ operatorname{ P}( X\ leq x)} and sometimes also using a probability density function, p X{\displaystyle p_{X.
In the field of statistical physics,a non-formal reformulation of the relation above between the derivative of the cumulative distribution function and the probability density function is generally used as the definition of the probability density function. .
The POISSON() function returns the Poisson distribution.
This is the probability mass function of the Poisson distribution with expected value λ.
The NORMSDIST() function returns the standard normal distribution.
So what I'm going to do is show you the distribution of matter as a function of scales.
In statistics,the delta method is a result concerning the approximate probability distribution for a function of an asymptotically normal statistical estimator from knowledge of the limiting variance of that estimator.