Results 231 to 240 of about 769,155 (267)
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Estimation of the pareto shape parameter
Communications in Statistics - Simulation and Computation, 2000The generalized jackknife is used to reduce the bias of an estimator, based on frequency moments, of the Pareto shape parameter. Computations of amount of bias reduction and simulations of mean-squared errors are presented.
Ennis Donice McCune, Sandra Luna McCune
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2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 2010
The basis function of B-spline of n order is extended to contain shape control parameter by integral, so that the shape of the constructed curve can be adjusted by changing the parameter value and it possesses the structure and geometry properties analogous to B-spline curve.
null Wei Chen +2 more
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The basis function of B-spline of n order is extended to contain shape control parameter by integral, so that the shape of the constructed curve can be adjusted by changing the parameter value and it possesses the structure and geometry properties analogous to B-spline curve.
null Wei Chen +2 more
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On testing a shape parameter in the presence of a location and a scale parameter
Series Statistics, 1978A test on a shape parameter in the presence of two nuisance parameters (a location parameter μ and a scale parameter σ)is proposed. Explicit formulas and approximations are given for three applications where the general and restricted distributions are:Student-vs-Gauss-distribution, λ-vs logistic distribution, and type Iior III vs.
van Montfort, M.A.J., Otten, A.
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Estimation of the shape parameter for the three-parameter Weibull distribution
Journal of Information and Optimization Sciences, 2001We propose the approximate maximum likelihood estimator (AMLE) for the shape parameter β in the three-parameter Weibull distribution based on Type-II right censored samples.
Suk-Bok Kang +2 more
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Parameter Estimation of the Shape Parameter of the Castillo–Hadi Model
Communications in Statistics - Theory and Methods, 2005Abstract In Castillo and Hadi [Castillo, E., Hadi, A. S. (1995). Modeling lifetime data with application to fatigue models. J. Amer. Statist. Assoc. 90:1041–1054], a new model for the analysis of lifetime data in the presence of a covariate is presented. The model is derived based on physical and statistical considerations. In this article, we focus on
Hideki Nagatsuka, Toshinari Kamakura
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Shape-Adjustable Generalized Bézier Rotation Surfaces with Multiple Shape Parameters
Results in Mathematics, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hu, Gang, Wei, Guo, Wu, Junli
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Parameter-free modelling of 2D shapes with ellipses
Pattern Recognition, 2016Our goal is to represent a given 2D shape with an automatically determined number of ellipses, so that the total area covered by the ellipses is equal to the area of the original shape without any assumption or prior knowledge about the object structure.
Costas Panagiotakis, Antonis A. Argyros
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Quadrilateral and hexahedron shape parameters
Finite Elements in Analysis and Design, 1994This paper determines quadrilateral and hexahedron shape parameters using the coefficients of basic shape functions. Examples and illustrations are presented. It is a complete theoretical study.
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Geometric Continuity and Shape Parameters
2013Given the two curves Q 1(u) and Q 2(u), consider the joint \(\frac{{{\text{Q}}_1 \left( u \right)}} {{{\text{Q}}_2 \left( u \right)}}\). Recalling equation (4.1), continuity of the unit tangent vector is achieved if $$\frac{{{\text{Q}}_1^{\left( 1 \right)} \left( 1 \right)}} {{\left| {{\text{Q}}_1^{\left( 1 \right)} \left( 1 \right)} \right ...
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Likelihood-Based Inference for the Shape Parameter of a Two Parameter Weibull Distribution
Lifetime Data Analysis, 2004Based on a Type 2 censored sample, we use the likelihood-based approach to draw likelihood inference on the shape parameter gamma of a two-parameter Weibull distribution. In particular, we derive the profile, conditional and marginal likelihoods of gamma. Numerical results along with some concluding remarks regarding the use of likelihood-based methods
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