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A unifying probability density function

by Gary R. Waissi - Applied Mathematics Letters , 1993
"... Abstract-This paper presents a new unifying continuous probability density function. It is shown that the continuous distributions Weibull-, gamma, Erlang-, x2 and exponential distributions can be derived from the proposed density function. 1. ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Abstract-This paper presents a new unifying continuous probability density function. It is shown that the continuous distributions Weibull-, gamma, Erlang-, x2 and exponential distributions can be derived from the proposed density function. 1.

Functional Models and Probability Density Functions

by Javier Nunez-Garcia, Olaf Wolkenhauer
"... There exist many approaches to discern a functional relationship between two variables. A functional model is useful for two reasons: Firstly, if the function is a relatively simple model in the plane, it provides us with qualitative information about the relationship. Secondly, given a fixed va ..."
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value for one variable, the other one can be calculated as a means for prediction. In this paper an approach for the extraction of functional models from probability density functions is proposed. The transformation of the conditional probability density function into a single value or a set

Composition of Probability Density Functions - Optimizing Approach

by J. Kracík - of International Series on Advanced Intelligence , 2004
"... This paper deals with composition of probability density functions (pdfs) in a sense of composition ..."
Abstract - Cited by 12 (2 self) - Add to MetaCart
This paper deals with composition of probability density functions (pdfs) in a sense of composition

On the probability density function of baskets

by Christian Bayer, Peter K. Friz, Peter Laurence , 2013
"... Abstract. The state price density of a basket, even under uncorrelated Black–Scholes dynamics, does not allow for a closed from density. (This may be rephrased as statement on the sum of lognormals and is especially annoying for such are used most frequently in Financial and Actuarial Mathematics.) ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
Abstract. The state price density of a basket, even under uncorrelated Black–Scholes dynamics, does not allow for a closed from density. (This may be rephrased as statement on the sum of lognormals and is especially annoying for such are used most frequently in Financial and Actuarial Mathematics

Probability density function

by Tzyy Shan Lin, Andrzej S. Nowak , 1983
"... Structural reliability depends on uncertainties in resistance and loads. In many practical cases the resistance dominates and a reduction of uncertainty about resistance isan effective way of increasing safety. It can be accomplished by proof loading. A truncated istribution is considered and reliab ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Structural reliability depends on uncertainties in resistance and loads. In many practical cases the resistance dominates and a reduction of uncertainty about resistance isan effective way of increasing safety. It can be accomplished by proof loading. A truncated istribution is considered and reliability indices are calculated for various proof load levels. The structural reliability is sensitive to proof loading for larger coefficients of variation of resistance. A Bayesian approach is applied to develop aposterior distribution for resistance, after proof loading. Reliability indices are calculated for various ratios of the coefficients of variation of load and resistance.

Uncertainty parameter · Probability density function

by László Varga, Botond Szabó, István Gy. Zsély, András Zempléni, Tamás Turányi, L. Varga, B. Szabó, A. Zempléni
"... Abstract The temperature dependence of rate coefficient k is usually described by the Arrhenius expression ln k = ln A − (E/R)T −1. Chemical kinetics databases contain the recommended values of Arrhenius parameters A and E, the uncertainty parameter f (T) of the rate coefficient and temperature rang ..."
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ln A and E/R, which is in accordance with their 2D normal probability density function (pdf). The upper and the lower edges of the 1D normal distribution of ln k correspond to the two opposite edge regions of the 2D pdf of the transformed Arrhenius parameters. Changing the temperature, these edge

probability density function system matrix for PET

by For Pet, Rutao Yao, Ranjith M Ramach, Neeraj Mahajan, Vinay Rathod, Noel Gunasekar, Ashish Panse, Tianyu Ma, Yiqiang Jian, Jianhua Yan, Richard E Carson , 2012
"... Assessment of a three-dimensional line-of-response probability density function system matrix ..."
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Assessment of a three-dimensional line-of-response probability density function system matrix

Approximating probability density functions with mixtures of truncated exponentials

by Barry R. Cobb, Prakash P. Shenoy - Proceedings of the Tenth Conference on Information Processing and Management of Uncertainty in KnowledgeBased Systems (IPMU-04), 2004
"... Mixtures of truncated exponentials (MTE) potentials are an alterna-tive to discretization for approx-imating probability density func-tions (PDF’s). This paper presents MTE potentials that approximate standard PDF’s and applications of these potentials for solving inference problems in hybrid Bayesi ..."
Abstract - Cited by 32 (21 self) - Add to MetaCart
Mixtures of truncated exponentials (MTE) potentials are an alterna-tive to discretization for approx-imating probability density func-tions (PDF’s). This paper presents MTE potentials that approximate standard PDF’s and applications of these potentials for solving inference problems in hybrid

Riemannian analysis of probability density functions with applications in vision

by Anuj Srivastava, Ian Jermyn, Shantanu Joshi - In 2007 IEEE CVPR’07 , 2007
"... Applications in computer vision involve statisti-cally analyzing an important class of constrained, non-negative functions, including probability density func-tions (in texture analysis), dynamic time-warping func-tions (in activity analysis), and re-parametrization or non-rigid registration functio ..."
Abstract - Cited by 51 (5 self) - Add to MetaCart
Applications in computer vision involve statisti-cally analyzing an important class of constrained, non-negative functions, including probability density func-tions (in texture analysis), dynamic time-warping func-tions (in activity analysis), and re-parametrization or non-rigid registration

Probability Density Functions in Program Analysis

by Dave Mason
"... The component reliability model described in [4] requires that component execution frequency, reliability, and transformations be analysed statistically based on parameters to the component. This paper describes work in progress toward that goal. ..."
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The component reliability model described in [4] requires that component execution frequency, reliability, and transformations be analysed statistically based on parameters to the component. This paper describes work in progress toward that goal.
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