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Probability and Density Functions

2021
This chapter deals with discussion of important probability density functions used in practice.
Chandrasekhar Putcha   +2 more
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THE MARGINAL PROBABILITY DENSITY FUNCTIONS OF WISHART PROBABILITY DENSITY FUNCTION

Far East Journal of Theoretical Statistics, 2018
Summary: Here we directly evaluate an \(\begin{pmatrix}{m+1}\\{2}\end{pmatrix}\)-dimensional integral \[ \int_{\mathbf{S}_{m}>0}|\mathbf{S}_m|^{\frac{n-m}{2}-1}\exp(-\mathrm{tr}(\mathbf{S}_{\mathbf{m}}))\mathrm{d}\mathbf{S}_m \] as an integral representation of Wishart multivariate gamma function \(\Gamma_m\left(\frac{n-1}{2}\right)\), by deriving the ...
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Probability Density Functions

2019
Abstract This chapter builds on probability distributions. Its focus is on general concepts associated with probability density functions (pdf’s), which are distributions associated with continuous random variables. The continuous uniform and normal distributions are highlighted as examples of pdf’s.
Therese M. Donovan, Ruth M. Mickey
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Probability density functions of soft information

IEEE Communications Letters, 2002
It is well known that soft decoding algorithms are based on the use of reliability measures for binary and nonbinary symbols. We consider an analytical estimation of the distributions of reliability measures after soft decoding of block and convolutional codes or intersymbol interference (ISI) channels.
REGGIANI, LUCA, TARTARA, GUIDO
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Estimation of a certain functional of a probability density function

Scandinavian Actuarial Journal, 1969
Abstract In nonparametric inference, the importance of the functional Δ(F)=∫−∞∞ ƒ2(x)dx, where F is the population cdf with density f, could hardly be overemphasized. It is a fundamental quantity involved in the expressions for the asymptotic efficiency of rank tests for many problems like location shift, regression, dependence, analysis of variance ...
Bhattacharyya, G. K., Roussas, G. G.
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Navier-stokes probability density function

European Journal of Mechanics - B/Fluids, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Minotti, F. O., Ferro Fontán, C.
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ON THE DENSITIES OF PROBABILITY MEASURES IN FUNCTION SPACES

Russian Mathematical Surveys, 1966
CONTENTSIntroduction § 1. Basic facts from the theory of stochastic processes § 2. Characteristic functionals of stochastic processes § 3. General theorems on the absolute continuity of probability measures in function spaces § 4. Absolute continuity of Gaussian measures in Hilbert space § 5.
Gikhman, I. I., Skorokhod, A. V.
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Estimation of probability density and distribution functions

IEEE Transactions on Information Theory, 1968
First- and second-order stochastic gradient algorithms are developed for suitably approximating the unknown density and distribution functions of a random vector from a sequence of independent samples. The mean-square-error criterion and the integral-square-error criterion are used in the approximations.
R. L. Kashyap, Colin C. Blaydon
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On system failure probability density function

Reliability Engineering & System Safety, 2007
Abstract The assessment of the system unreliability is usually accomplished through well-known tools such as block diagram, fault tree, Monte Carlo and others. These methods imply the knowledge of the failure probability density function of each component “k” (pdf p k ).
Campioni L., VESTRUCCI, PAOLO
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Cluster Width of probability Density functions

Intelligent Data Analysis, 2019
This study establishes the new results for Cluster Width of probability Density functions (CWD). There are the upper and lower bounds of CWD and the relationships of CWD to other measures in statistical discriminant. The CWD for two and more two probability density functions is determined in the different cases.
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