Least squares fitting the three-parameter inverse Weibull density [PDF]
, 2010 The inverse Weibull model was developed by Erto [10]. In practice, the unknown parameters of the appropriate inverse Weibull density are not known and must be estimated from a random sample.
Darija Marković +2 more
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Least-squares fitting of parametric curves with a linear function of several variables as argument [PDF]
, 1998 We discuss fitting of a parametric curve in the plane in the least-squares sense when the independent variable is a linear function of several variables with unknown coefficients. A general numerical method is recommended.
H. Späth
core +1 more source
Data fitting with a set of two concentric spheres [PDF]
, 2006 We consider fitting data points in space by a set of two concentric spheres. This problem ought to occur within computational metrology.
H. Späth
core +1 more source
A Levinson-Galerkin algorithm for regularized trigonometric approximation
, 1999 Trigonometric polynomials are widely used for the approximation of a smooth function $f$ from a set of nonuniformly spaced samples $\{f(x_j)\}_{j=0}^{N-1}$.
Strohmer, Thomas
core +3 more sources
Constrained reconstruction of 3D curves and surfaces using integral spline operators [PDF]
, 2013 In the context of direct/reverse engineering processes one of the main problem is the reconstruction of curves and surfaces starting from a cloud of points.
E. Miglio, F. Caliò
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Least squares fitting with rotated paraboloids [PDF]
, 2001 In [1] the problem of estimating the parameters of a rotated parabola fitted to measured points in the plane was examined. The corresponding method, also used in [2,3], is extended here to the case of a rotated paraboloid.
H. Späth
core
Least orthogonal absolute deviations problem for generalized logistic function [PDF]
, 1997 We consider the existence of optimal parameters for generalized logistic model by least orthogonal absolute deviations, and prove the existence of such optimal solution, under the monotonicity condition on the ...
T. Marošević
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Optimal bandwidth selection for semi-recursive kernel regression estimators
, 2016 In this paper we propose an automatic selection of the bandwidth of the semi-recursive kernel estimators of a regression function defined by the stochastic approximation algorithm.
Slaoui, Yousri
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Fitting affine and orthogonal transformations between two sets of points [PDF]
, 2004 Let two point sets P and Q be given in $R^n$. We determine a translation and an affine transformation or an isometry such that the image of Q approximates P as best as possible in the least squares ...
H. Späth
core
Shape restricted regression with random Bernstein polynomials
, 2007 Shape restricted regressions, including isotonic regression and concave regression as special cases, are studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods.
Chang, I-Shou +4 more
core +1 more source