Примеры использования Probability distributions на Английском языке и их переводы на Русский язык
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Probability distributions.
Continuous probability distributions.
Import an entity store with data about univariate probability distributions.
Normal probability distributions.
Different random graph models produce different probability distributions on graphs.
The probability distributions(Giry) monad.
This script plots the normal-, binomial- and chisquare probability distributions;
There are 465 probability distributions in this store.
In mathematics, random graph is the general term to refer to probability distributions over graphs.
We transform the probability distributions related to a given hidden Markov model into matrix notation as follows.
Analyze datasets of almost unlimited size with a variety of statistics operations and probability distributions.
In particular, we can expect to assign probability distributions to propositions such as{a≤ speed≤ b.
MDL is very strongly connected to probability theory andstatistics through the correspondence between codes and probability distributions mentioned above.
Assume that the probability distributions P{\displaystyle P} and Q{\displaystyle Q} are both parameterized by some(possibly multi-dimensional) parameter θ{\displaystyle\theta.
Central to MDL theory is the one-to-one correspondence between code length functions and probability distributions this follows from the Kraft-McMillan inequality.
Not all classification models are naturally probabilistic, and some that are, notably naive Bayes classifiers, decision trees and boosting methods,produce distorted class probability distributions.
The application possibilities for exact and limit probability distributions of statistics are considered, and could be used further for fitting criterion creation within symbolic data analysis.
Statistics, Further Differentiation, Trigonometric Identities, Functions, Probability, Correlation andLinear Regression, Probability Distributions, Further Integration.
A particular focus of his work was the construction of logical principles for assigning prior probability distributions; see the principle of maximum entropy, the principle of transformation groups and Laplace's principle of indifference.
Wolfram Finance Platform's high-level language includes support for a wide range of computational tools, such as derivatives pricing, model analysis, optimization methods,time series, probability distributions and statistical tests.
In other cases, such as"taking a random integer" or"taking a random real number",there are no probability distributions at all symmetric with respect to relabellings or to exchange of equally long subintervals.
Non-parametric(or distribution-free) inferential statistical methods are mathematical procedures for statistical hypothesis testing which, unlike parametric statistics,make no assumptions about the probability distributions of the variables being assessed.
In the method, local rules of photon transport are expressed as probability distributions which describe the step size of photon movement between sites of photon-tissue interaction and the angles of deflection in a photon's trajectory when a scattering event occurs.
Parameters of this type are given names appropriate to their roles, including the following. location parameter dispersion parameter orscale parameter shape parameter Where a probability distribution has a domain over a set of objects that are themselves probability distributions, the term concentration parameter is used for quantities that index how variable the outcomes would be.
For the input stream with a variable parameter put in the systemwith unlimited service the probability distributions and numerical characteristics for the sums of maxima of the requirement increments received and served in a finite period of time were found in terms of characteristic functions.
Probability distributions and numerical specifications for the sums of maxima of exponential price increments of received and served customers' applications about sales in the period of employment have been found for the simplest Poisson input into the queuing system without delay and with constant holding time.
Arthur Hobson proved that the Kullback-Leibler divergence is the only measure of difference between probability distributions that satisfies some desired properties, which are the canonical extension to those appearing in a commonly used characterization of entropy.
The cross entropy between two probability distributions measures the average number of bits needed to identify an event from a set of possibilities, if a coding scheme is used based on a given probability distribution q, rather than the"true" distribution pp.
In information theory, the cross entropy between two probability distributions p{\displaystyle p} and q{\displaystyle q} over the same underlying set of events measures the average number of bits needed to identify an event drawn from the set if a coding scheme used for the set is optimized for an estimated probability distribution q{\displaystyle q}, rather than the true distribution p{\displaystyle p.
Probability distribution of annual recruitment and population parameters.