Fitting circles to scattered data: parameter estimates have no moments

نویسنده

  • N. Chernov
چکیده

We study a nonlinear regression problem of fitting a circle (or a circular arc) to scattered data. We prove that under any standard assumptions on the statistical distribution of errors that are commonly adopted in the literature, the estimates of the circle center and radius have infinite moments. We also discuss methodological implications of this fact.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Classical and Bayesian Inference in Two Parameter Exponential Distribution with Randomly Censored Data

Abstract. This paper deals with the classical and Bayesian estimation for two parameter exponential distribution having scale and location parameters with randomly censored data. The censoring time is also assumed to follow a two parameter exponential distribution with different scale but same location parameter. The main stress is on the location parameter in this paper. This parameter has not...

متن کامل

Fitting circles to data with correlated noise

We study the problem of fitting circles to scattered data. Unlike many other studies, we assume that the noise is (strongly) correlated; we adopt a particular model where correlations decay exponentially with the distance between data points. Our main results are formulas for the maximum likelihood estimates and their covariance matrix. Our study is motivated by (and applied to) arcs collected ...

متن کامل

Three-parameter Kappa distribution and its fitting to the whole monthly rainfall data of Abali station in Tehran province

Kappa distribution is a positively skewed distribution which is used in analyzing precipitation, wind speed and streamflow data. In this paper, first a three-parameter Kappa distribution that introduced by Park et al. (2009) is studied and then four different methods of estimation including Moments, L-Moments, Maximum Likelihood and Maximum Product Spacing Method are presented in order to estim...

متن کامل

Comparison of GLD Fitting Methods: Superiority of Percentile Fits to Moments in L^2 Norm

The flexibility of the family of Generalized Lambda Distributions (GLD) has encouraged researchers to fit GLD distributions to datasets in many circumstances. The methods that have been used to obtain GLD fits have also varied. This paper compares, for the first time, the relative qualities of three GLD fitting methods: the method of moments, a method based on percentiles, and a method that use...

متن کامل

On 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 کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009