NONLINEARITY AND LEAST SQUARES

CISM journal ◽  
1988 ◽  
Vol 42 (4) ◽  
pp. 321-330 ◽  
Author(s):  
P.J.G. Teunissen ◽  
E.H. Knickmeyer
Keyword(s):  
Least Squares ◽  
Covariance Structure ◽  
Point Of View ◽  
Helmert Transformation ◽  
Know How ◽  
Least Squares Estimators ◽  
Functional Relations ◽  
Geometric Point ◽  
Rotational Invariant ◽  
Almost All

Since almost all functional relations in our geodetic models are nonlinear, it is important, especially from a statistical inference point of view, to know how nonlinearity manifests itself at the various stages of an adjustment. In this paper particular attention is given to the effect of nonlinearity on the first two moments of least squares estimators. Expressions for the moments of least squares estimators of parameters, residuals and functions derived from parameters, are given. The measures of nonlinearity are discussed both from a statistical and differential geometric point of view. Finally, our results are applied to the 2D symmetric Helmert transformation with a rotational invariant covariance structure.

scholarly journals Least-Squares Estimators of Drift Parameter for Discretely Observed Fractional Ornstein–Uhlenbeck Processes

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 716 ◽  
Author(s):  
Pavel Kříž ◽  
Leszek Szała
Keyword(s):  
Brownian Motion ◽  
Least Squares ◽  
Fractional Brownian Motion ◽  
Numerical Experiments ◽  
Covariance Structure ◽  
Mesh Size ◽  
Uhlenbeck Process ◽  
Least Squares Estimators ◽  
Discrete Time Observations ◽  
Drift Parameter

We introduce three new estimators of the drift parameter of a fractional Ornstein–Uhlenbeck process. These estimators are based on modifications of the least-squares procedure utilizing the explicit formula for the process and covariance structure of a fractional Brownian motion. We demonstrate their advantageous properties in the setting of discrete-time observations with fixed mesh size, where they outperform the existing estimators. Numerical experiments by Monte Carlo simulations are conducted to confirm and illustrate theoretical findings. New estimation techniques can improve calibration of models in the form of linear stochastic differential equations driven by a fractional Brownian motion, which are used in diverse fields such as biology, neuroscience, finance and many others.

scholarly journals A New Inverted Topp-Leone Distribution: Applications to the COVID-19 Mortality Rate in Two Different Countries

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 25 ◽  
Author(s):  
Ehab Almetwally ◽  
Randa Alharbi ◽  
Dalia Alnagar ◽  
Eslam Hafez
Keyword(s):  
Statistical Model ◽  
Least Squares ◽  
Weighted Least Squares ◽  
Likelihood Estimation ◽  
Linear Representation ◽  
Rate Function ◽  
Estimation Methods ◽  
Unknown Parameters ◽  
Least Squares Estimators ◽  
New Distribution

This paper aims to find a statistical model for the COVID-19 spread in the United Kingdom and Canada. We used an efficient and superior model for fitting the COVID 19 mortality rates in these countries by specifying an optimal statistical model. A new lifetime distribution with two-parameter is introduced by a combination of inverted Topp-Leone distribution and modified Kies family to produce the modified Kies inverted Topp-Leone (MKITL) distribution, which covers a lot of application that both the traditional inverted Topp-Leone and the modified Kies provide poor fitting for them. This new distribution has many valuable properties as simple linear representation, hazard rate function, and moment function. We made several methods of estimations as maximum likelihood estimation, least squares estimators, weighted least-squares estimators, maximum product spacing, Crame´r-von Mises estimators, and Anderson-Darling estimators methods are applied to estimate the unknown parameters of MKITL distribution. A numerical result of the Monte Carlo simulation is obtained to assess the use of estimation methods. also, we applied different data sets to the new distribution to assess its performance in modeling data.

scholarly journals How ethical challenges of covert observations can be met in practice

2021 ◽  
pp. 174701612110082
Author(s):  
Nicole Podschuweit
Keyword(s):  
Social Research ◽  
Role Playing ◽  
Great Distance ◽  
Point Of View ◽  
Ethical Challenges ◽  
Research Subjects ◽  
Written Information ◽  
Ethical Debate ◽  
The People ◽  
Almost All

This paper aims to bring into the ethical debate on covert research two aspects that are neglected to date: the perspective of the research subjects and the special responsibility of investigators towards their observers. Both aspects are falling behind, especially in quantitative social research. From a methodological point of view, quantitative forms of covert observation involve a great distance between the researcher and the research subjects. When human observers are involved, the focus is usually on the reliable application of the measuring instrument. Therefore, herein, a quantitative study is used as an example to show how the protection needs of both the observed persons and the observers can be met in practice. The study involved 40 student observers who covertly captured everyday conversations in real-world settings (e.g. in cafés or trains) by a highly standardised observation scheme. The study suggests that the anonymity of the research subjects and their trust in the observers are crucial for their subsequent consent. However, many participants showed only little or even no interest in the written information they were provided. Further, this study strongly emphasises how mentally stressful covert observations are to the observers. Almost all observers were worried in advance that the people they were observing would prematurely blow their cover and confront them. Role-playing and in-depth discussions in teams are good strategies to alleviate such and other fears and to prepare student assistants well for their demanding work in the field.

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