The problem of fitting surfaces to data is a well studied problem in statistics. However when there is prior information the theory is not developed. It often happens in toxicology and in medicine that the effect of a single drug is well understood.. However if a pair of drugs is delivered in tandem or if two toxins are interacting the effect is not understood. In this paper we attack the problem of fitting a surface to a data set contained in a square when two of the boundaries are known. Our approach generalizes the concept of smoothing splines.Godkänd; 2004; 20070107 (ysko
We present an extension of the functional data analysis framework for univariate functions to the an...
This paper looks into the effectiveness of B-spline approximation algorithm in approximating the bic...
Parametric spline surfaces represent an important surface type in the process of reverse engineering...
The problem of fitting surfaces to data is a well studied problem in statistics. However when there ...
AbstractConvexity conditions for Powell—Sabin splines are derived and an algorithm is presented for ...
Surface fitting and smoothing splines techniques are widely used in practice to fit data arising fro...
Estimation of support frontiers and boundaries often involves monotone and/or concave edge data smoo...
AbstractSpline smoothing is a very good technique to fit a surface to a noisy scattered data set. Su...
We present a method for estimating functions on topologically and/or geometrically complex surfaces...
This work considers the fitting of data points organized in a rectangular array to parametric spline...
We have investigated the estimation of 2-D boundary functions from sampled data sets where both nois...
This thesis is concerned with the design and implementation of a surface fitting package in an inter...
Most approaches to least squares fitting of a B-spline surface to measurement data require a paramet...
A method is developed for fitting smooth curves through a series of shapes of landmarks in two dimen...
Non-uniform rational B-spline (NURBS) surface fitting from data points is wildly used in the fields ...
We present an extension of the functional data analysis framework for univariate functions to the an...
This paper looks into the effectiveness of B-spline approximation algorithm in approximating the bic...
Parametric spline surfaces represent an important surface type in the process of reverse engineering...
The problem of fitting surfaces to data is a well studied problem in statistics. However when there ...
AbstractConvexity conditions for Powell—Sabin splines are derived and an algorithm is presented for ...
Surface fitting and smoothing splines techniques are widely used in practice to fit data arising fro...
Estimation of support frontiers and boundaries often involves monotone and/or concave edge data smoo...
AbstractSpline smoothing is a very good technique to fit a surface to a noisy scattered data set. Su...
We present a method for estimating functions on topologically and/or geometrically complex surfaces...
This work considers the fitting of data points organized in a rectangular array to parametric spline...
We have investigated the estimation of 2-D boundary functions from sampled data sets where both nois...
This thesis is concerned with the design and implementation of a surface fitting package in an inter...
Most approaches to least squares fitting of a B-spline surface to measurement data require a paramet...
A method is developed for fitting smooth curves through a series of shapes of landmarks in two dimen...
Non-uniform rational B-spline (NURBS) surface fitting from data points is wildly used in the fields ...
We present an extension of the functional data analysis framework for univariate functions to the an...
This paper looks into the effectiveness of B-spline approximation algorithm in approximating the bic...
Parametric spline surfaces represent an important surface type in the process of reverse engineering...