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Displaying similar documents to “Reference points based recursive approximation”

Reference points based transformation and approximation

Csaba Török (2013)

Kybernetika

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Interpolating and approximating polynomials have been living separately more than two centuries. Our aim is to propose a general parametric regression model that incorporates both interpolation and approximation. The paper introduces first a new r -point transformation that yields a function with a simpler geometrical structure than the original function. It uses r ≥ 2 reference points and decreases the polynomial degree by r - 1 . Then a general representation of polynomials is proposed based...

Limits of Bayesian decision related quantities of binomial asset price models

Wolfgang Stummer, Wei Lao (2012)

Kybernetika

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We study Bayesian decision making based on observations X n , t : t ∈ { 0 , T n , 2 T n , ... , n T n } ( T > 0 , n ∈ ℕ ) of the discrete-time price dynamics of a financial asset, when the hypothesis a special n -period binomial model and the alternative is a different n -period binomial model. As the observation gaps tend to zero (i. e. n → ∞ ), we obtain the limits of the corresponding Bayes risk as well as of the related Hellinger integrals and power divergences. Furthermore, we also give an example for the “non-commutativity” between Bayesian statistical...

Full-Newton step infeasible interior-point algorithm for SDO problems

Hossein Mansouri (2012)

Kybernetika

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In this paper we propose a primal-dual path-following interior-point algorithm for semidefinite optimization. The algorithm constructs strictly feasible iterates for a sequence of perturbations of the given problem and its dual problem. Each main step of the algorithm consists of a feasibility step and several centering steps. At each iteration, we use only full-Newton step. Moreover, we use a more natural feasibility step, which targets at the μ + -center. The iteration bound of the algorithm...