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Reference points based recursive approximation

Martina Révayová, Csaba Török (2013)

Kybernetika

The paper studies polynomial approximation models with a new type of constraints that enable to get estimates with significant properties. Recently we enhanced a representation of polynomials based on three reference points. Here we propose a two-part cubic smoothing scheme that leverages this representation. The presence of these points in the model has several consequences. The most important one is the fact that by appropriate location of the reference points the resulting approximant of two...

Reference points based transformation and approximation

Csaba Török (2013)

Kybernetika

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 on r ≥ 1 reference...

Reflexiones sobre la estrategia de medida de los cambios en probabilidad en modelos de elección binarios.

M.ª Teresa Aparicio Aspas, Inmaculada Villanúa Martín (1998)

Qüestiió

Este trabajo se centra en la evaluación de la medida que, en el marco de los modelos de elección binarios o dicotómicos, se utiliza para reflejar el cambio en la probabilidad ante la variación de una de las variables explicativas. La opción de cuantificación más común ha consistido en utilizar el vector de valores medios de las variables explicativas, lo que podemos entender como poner el énfasis en el comportamiento de un "individuo medio". Frente a esta práctica habitual, efectuamos una propuesta...

Regions of stability for ill-posed convex programs: An addendum

Sanjo Zlobec (1986)

Aplikace matematiky

The marginal value formula in convex optimization holds in a more restrictive region of stability than that recently claimed in the literature. This is due to the fact that there are regions of stability where the Lagrangian multiplier function is discontinuous even for linear models.

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