Best Poisson Approximation of Poisson Mixtures. A Linear Operator Approach

2005 ◽  
pp. 1-12 ◽  
Author(s):  
José Antonio Adell ◽  
Alberto Lekuona
Keyword(s):  
Linear Operator ◽  
Poisson Approximation ◽  
Operator Approach ◽  
Poisson Mixtures

Poisson approximation of multivariate Poisson mixtures

2003 ◽  
Vol 40 (02) ◽  
pp. 376-390 ◽  
Author(s):  
Bero Roos
Keyword(s):  
Total Variation ◽  
Poisson Approximation ◽  
Upper Bounds ◽  
Risk Theory ◽  
Total Variation Distance ◽  
Poisson Mixtures ◽  
Poisson Distributions ◽  
Variation Distance

We show how good multivariate Poisson mixtures can be approximated by multivariate Poisson distributions and related finite signed measures. Upper bounds for the total variation distance with applications to risk theory and generalized negative multinomial distributions are given. Furthermore, it turns out that the ideas used in this paper also lead to improvements in the Poisson approximation of generalized multinomial distributions.

scholarly journals A linear operator approach to succession rules

2002 ◽  
Vol 348 (1-3) ◽  
pp. 231-246 ◽  
Author(s):  
Luca Ferrari ◽  
Renzo Pinzani
Keyword(s):  
Linear Operator ◽  
Operator Approach

Poisson approximation of multivariate Poisson mixtures

2003 ◽  
Vol 40 (2) ◽  
pp. 376-390 ◽  
Author(s):  
Bero Roos
Keyword(s):  
Total Variation ◽  
Poisson Approximation ◽  
Upper Bounds ◽  
Risk Theory ◽  
Total Variation Distance ◽  
Poisson Mixtures ◽  
Poisson Distributions ◽  
Variation Distance

We show how good multivariate Poisson mixtures can be approximated by multivariate Poisson distributions and related finite signed measures. Upper bounds for the total variation distance with applications to risk theory and generalized negative multinomial distributions are given. Furthermore, it turns out that the ideas used in this paper also lead to improvements in the Poisson approximation of generalized multinomial distributions.

scholarly journals Sharp estimates in signed Poisson approximation of Poisson mixtures

Bernoulli ◽  
2005 ◽  
Vol 11 (1) ◽  
pp. 47-65 ◽  
Author(s):  
José Antonio Adell ◽  
Alberto Lekuona
Keyword(s):  
Poisson Approximation ◽  
Sharp Estimates ◽  
Poisson Mixtures

Impact of Linear Operator on the Convergence of HAM Solution: a Modified Operator Approach

2016 ◽  
Vol 8 (3) ◽  
pp. 499-516 ◽  
Author(s):  
S. T. Hussain ◽  
S. Nadeem ◽  
M. Qasim
Keyword(s):  
Linear Operator ◽  
Linear Operators ◽  
Computational Time ◽  
Computational Process ◽  
Analysis Method ◽  
Operator Approach ◽  
Flow Problems ◽  
Homotopy Analysis ◽  
Effective Use ◽  
Parameter Dependent

Abstract.The linear operator plays an important role in the computational process of Homotopy Analysis Method (HAM). In HAM frame any kind of linear operator can be chosen to develop a solution. Hence, it is easy to introduce the modified/physical parameter dependent linear operators. The effective use of these operators has been judged through solving fluid flow problems. Modification in linear operators affects the solution and improves the computational efficiency of HAM for larger values of parameters. The convergence rate of the solution is rapid and several times higher resulting in lesser computational time.

Operator approach for orthogonality in linear spaces

2018 ◽  
Vol 11 (4) ◽  
pp. 103-112
Author(s):  
Mahdi Iranmanesh ◽  
Maryam Saeedi Khojasteh
Keyword(s):  
Operator Approach ◽  
Linear Spaces

Functional Ross Recovery: An Operator Approach

2017 ◽  
Author(s):  
Yannick Dillschneider ◽  
Raimond Maurer
Keyword(s):  
Operator Approach

A note on normal operators

1963 ◽  
Vol 59 (4) ◽  
pp. 727-729 ◽  
Author(s):  
S. J. Bernau ◽  
F. Smithies
Keyword(s):  
Hilbert Space ◽  
Linear Operator ◽  
Adjoint Operator ◽  
Spectral Theorem ◽  
Unitary Operators ◽  
Unitary Space ◽  
Bounded Linear ◽  
Finite Dimensional ◽  
Normal Operators ◽  
Finite Dimensional Case

We recall that a bounded linear operator T in a Hilbert space or finite-dimensional unitary space is said to be normal if T commutes with its adjoint operator T*, i.e. TT* = T*T. Most of the proofs given in the literature for the spectral theorem for normal operators, even in the finite-dimensional case, appeal to the corresponding results for Hermitian or unitary operators.

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