Statistical efficiency of curve fitting algorithms
نویسندگان
چکیده
منابع مشابه
Statistical efficiency of curve fitting algorithms
We study the problem of fitting parametrized curves to noisy data. Under certain assumptions (known as Cartesian and radial functional models), we derive asymptotic expressions for the bias and the covariance matrix of the parameter estimates. We also extend Kanatani’s version of the Cramer-Rao lower bound, which he proved for unbiased estimates only, to more general estimates that include many...
متن کاملOn the complexity of curve fitting algorithms
We study a popular algorithm for fitting polynomial curves to scattered data based on the least squares with gradient weights. We show that sometimes this algorithm admits a substantial reduction of complexity, and, furthermore, find precise conditions under which this is possible. It turns out that this is, indeed, possible when one fits circles but not ellipses or hyperbolas. In many applicat...
متن کاملCurve-fitting Algorithms for Shape Error Concealment
Introduction of Video Objects (VOs) is one of the major contributions of MPEG-4 to the previous MPEG standards. The a-plane of a VO defines its shape and hence determines the boundary of its texture. In error prone communication networks, shape information, as well as texture information is subject to bit error contamination. In this paper, we propose two post-processing shape concealment techn...
متن کاملStatistical efficiency of adaptive algorithms
The statistical efficiency of a learning algorithm applied to the adaptation of a given set of variable weights is defined as the ratio of the quality of the converged solution to the amount of data used in training the weights. Statistical efficiency is computed by averaging over an ensemble of learning experiences. A high quality solution is very close to optimal, while a low quality solution...
متن کاملMultiple Sequence Alignment Based Upon Statistical Approach of Curve Fitting
The main objective of our work is to align multiple sequences together on the basis of statistical approach in lieu of heuristics approach. Here we are proposing a novel idea for aligning multiple sequences in which we will be considering the DNA sequences as lines not as strings where each character represents a point in the line. DNA sequences are aligned in such a way that maximum overlap ca...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2004
ISSN: 0167-9473
DOI: 10.1016/j.csda.2003.11.008