Procrustean statistical inference of deformations

نویسندگان

  • E. Groten Technical University of Darmstadt Institute of Physical Geodesy Petersenstrasse 13, Darmstadt, Germany
  • M. Becker Technical University of Darmstadt Institute of Physical Geodesy Petersensrasse 13, Darmstadt, Germany
  • M. Mashhadi Hossainali Associate Professor ,Faculty of Geodesy and Geomatics Engineering, K.N.Toosi University of Technology, ,Tehran, Iran
چکیده مقاله:

A two step method has been devised for the statistical inference of deformation changes. In the first step of this method and based on Procrustes analysis of deformation tensors, the significance of the change in a time or space series of deformation tensors is statistically analyzed. In the second step significant change(s) in deformations are localized. In other words, they are assigned to certain parameters of deformation. This is done using the Global Model Test. Because of the key role of Procrustes analysis in the proposed method for the inference of deformation changes, it has been given the name of Procrustean Statistical Inference of Deformations. The method has been implemented to synthetic and real deformations. The 3D-deformation tensors of a regional GPS network in the Kenai Peninsular, for analyzing the spatial variation of deformation tensors, and a local GPS network in Alps, for analyzing the temporal variation of deformation tensors have been used for illustrating the practical application of the proposed method.

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Review of the Applications of Exponential Family in Statistical Inference

‎In this paper‎, ‎after introducing exponential family and a history of work done by researchers in the field of statistics‎, ‎some applications of this family in statistical inference especially in estimation problem‎,‎statistical hypothesis testing and statistical information theory concepts will be discussed‎.

متن کامل

Statistical Inference

At the heart of statistics lie the ideas of statistical inference. Methods of statistical inference enable the investigator to argue from the particular observations in a sample to the general case. In contrast to logical deductions made from the general case to the specific case, a statistical inference can sometimes be incorrect. Nevertheless, one of the great intellectual advances of the twe...

متن کامل

Statistical Inference

λn = f1(x1)f1(x2) · · · f1(xn) f0(x1)f0(x2) · · · f0(xn) where we have simplified the notation by writing f0(x) for f(x | θ0) and f1(x) for f(x | θ1). A Likelihoodist Statistician would find the likelihood ratio λn to be the best direct measure of the relative support of the data for these two hypotheses; a Bayesian statistician with prior probabilities π0 = P[H0] and π1 = P[H1] = (1−π0) would ...

متن کامل

Statistical Inference and Statistical Mechanics

In this lecture, recent developments on connections between Markov processes and nonequilibrium statistical mechanical systems are discussed. A statistical mechanical analogy is developed for Markov processes and a local entropic measure of their true asymmetry is defined. Introducing partial observations, conditional and joint analogies are developed for Markov processes and their optimal filt...

متن کامل

منابع من

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

ذخیره در منابع من قبلا به منابع من ذحیره شده

{@ msg_add @}


عنوان ژورنال

دوره 1  شماره 2

صفحات  31- 40

تاریخ انتشار 2016-12

با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.

کلمات کلیدی

میزبانی شده توسط پلتفرم ابری doprax.com

copyright © 2015-2023