A comparison of the variance estimation methods for heteroscedastic nonlinear models

2016 ◽  
Vol 35 (26) ◽  
pp. 4856-4874 ◽  
Author(s):  
Kurex Sidik ◽  
Jeffrey N. Jonkman
Keyword(s):  
Variance Estimation ◽  
Nonlinear Models ◽  
Estimation Methods

scholarly journals Combinatorial Algorithm In Linear Model

2018 ◽  
Vol 196 ◽  
pp. 03017
Author(s):  
Jana Ižvoltová ◽  
Peter Pisca
Keyword(s):  
Parameter Estimation ◽  
Linear Model ◽  
Markov Models ◽  
Nonlinear Models ◽  
The Other ◽  
Estimation Methods ◽  
Combinatorial Algorithm ◽  
Alternative Approach ◽  
Parameter Estimation Methods ◽  
Iterative Numerical Methods

Gauss-jacobi combinatorial algorithm is an alternative approach to traditional iterative numerical methods, which is primary oriented for parameter estimation in nonlinear models. The combinatorial algorithm is often exploited for outlier diagnosis in nonlinear models, where the other parameter estimation methods lose their efficiency. The paper describes comparison of both of gauss-jacobi combinatorial and gauss-markov models executed on parameter estimation process of levelling network for the reason to find the efficiency of combinatorial algorithm in simply linear model.

Nonlinear Models of Measurement Errors

2011 ◽  
Vol 49 (4) ◽  
pp. 901-937 ◽  
Author(s):  
Xiaohong Chen ◽  
Han Hong ◽  
Denis Nekipelov
Keyword(s):  
Economic Analysis ◽  
Instrumental Variable ◽  
Measurement Errors ◽  
Nonlinear Models ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Discrete Variables ◽  
Errors In Variables ◽  
Economic Data ◽  
Research Papers

Measurement errors in economic data are pervasive and nontrivial in size. The presence of measurement errors causes biased and inconsistent parameter estimates and leads to erroneous conclusions to various degrees in economic analysis. While linear errors-in-variables models are usually handled with well-known instrumental variable methods, this article provides an overview of recent research papers that derive estimation methods that provide consistent estimates for nonlinear models with measurement errors. We review models with both classical and nonclassical measurement errors, and with misclassification of discrete variables. For each of the methods surveyed, we describe the key ideas for identification and estimation, and discuss its application whenever it is currently available. (JEL C20, C26, C50)

scholarly journals Meta-Analysis with Robust Variance Estimation: Expanding the Range of Working Models

2020 ◽  
Author(s):  
James E Pustejovsky ◽  
Elizabeth Tipton
Keyword(s):  
Variance Estimation ◽  
Meta Analysis ◽  
Estimation Methods ◽  
Single Type ◽  
Dependence Structure ◽  
Dependent Effect ◽  
Working Models ◽  
Robust Variance ◽  
Robust Variance Estimation ◽  
Meta Regression

In prevention science and related fields, large meta-analyses are common, and these analyses often involve dependent effect size estimates. Robust variance estimation (RVE) methods provide a way to include all dependent effect sizes in a single meta-regression model, even when the nature of the dependence is unknown. RVE uses a working model of the dependence structure, but the two currently available working models are limited to each describing a single type of dependence. Drawing on flexible tools from multivariate meta-analysis, this paper describes an expanded range of working models, along with accompanying estimation methods, which offer benefits in terms of better capturing the types of data structures that occur in practice and improving the efficiency of meta-regression estimates. We describe how the methods can be implemented using existing software (the ‘metafor’ and ‘clubSandwich’ packages for R) and illustrate the approach in a meta-analysis of randomized trials examining the effects of brief alcohol interventions for adolescents and young adults.

scholarly journals Accurate Solution of Navigation Equations in GPS Receivers for Very High Velocities Using Pseudorange Measurements

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
N. Rahemi ◽  
M. R. Mosavi ◽  
A. A. Abedi ◽  
S. Mirzakuchaki
Keyword(s):  
Least Squares ◽  
Navigation System ◽  
Variance Estimation ◽  
Least Squares Method ◽  
Accurate Solution ◽  
Estimation Methods ◽  
Gps Receivers ◽  
The Earth ◽  
Exact Position ◽  
Very High

GPS is a satellite-based navigation system that is able to determine the exact position of objects on the Earth, sky, or space. By increasing the velocity of a moving object, the accuracy of positioning decreases; meanwhile, the calculation of the exact position in the movement by high velocities like airplane movement or very high velocities like satellite movement is so important. In this paper, seven methods for solving navigation equations in very high velocities using least squares method and its combination with the variance estimation methods for weighting observations based on their qualities are studied. Simulations on different data with different velocities from 100 m/s to 7000 m/s show that proposed method can improve the accuracy of positioning more than 50%.

scholarly journals Empirical Study of Travel Time Estimation and Reliability

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Ruimin Li ◽  
Huajun Chai ◽  
Jin Tang
Keyword(s):  
Travel Time ◽  
Time Distribution ◽  
Large Scale ◽  
Variance Estimation ◽  
Time Estimation ◽  
Estimation Methods ◽  
Travel Time Estimation ◽  
Time Variance ◽  
Travel Time Distribution ◽  
Average Travel Time

This paper explores the travel time distribution of different types of urban roads, the link and path average travel time, and variance estimation methods by analyzing the large-scale travel time dataset detected from automatic number plate readers installed throughout Beijing. The results show that the best-fitting travel time distribution for different road links in 15 min time intervals differs for different traffic congestion levels. The average travel time for all links on all days can be estimated with acceptable precision by using normal distribution. However, this distribution is not suitable to estimate travel time variance under some types of traffic conditions. Path travel time can be estimated with high precision by summing the travel time of the links that constitute the path. In addition, the path travel time variance can be estimated by the travel time variance of the links, provided that the travel times on all the links along a given path are generated by statistically independent distributions. These findings can be used to develop and validate microscopic simulations or online travel time estimation and prediction systems.

Estimating burn severity at the regional level using optically based indices

2011 ◽  
Vol 41 (4) ◽  
pp. 863-872 ◽  
Author(s):  
Mihai Tanase ◽  
Juan de la Riva ◽  
Fernando Pérez-Cabello
Keyword(s):  
Nonlinear Models ◽  
Regional Level ◽  
Estimation Methods ◽  
Burn Severity ◽  
Spectral Indices ◽  
Estimation Errors ◽  
Data Set ◽  
Pooled Data ◽  
Severity Estimation ◽  
Individual Site

During the last decades, the average number of fires per year increased significantly. A twofold increase was observed in the Mediterranean Basin, whereas in the western United States, the increase was fourfold. Regional models for burn severity estimation are necessary to avoid time consuming and costly fieldwork at each individual site. Furthermore, the estimation errors should be assessed by burn severity classes to avoid overestimating models accuracy. To develop such models, this study assessed the relationship between the composite burn index (CBI) and several spectral indices across five burned sites in northeastern Spain. The nonlinear models coupled with spectral indices containing information from the short wavelength infrared provided the best statistical fit of the data at most individual sites and for the pooled data set. The estimation errors for highly burned sites were well below 10%, but for burned sites of low and moderate severity, the errors increased significantly. A strong linear relation was found between burn severity at the plot level and understory and overstory composites. This study demonstrates (i) the model consistency at the regional level and (ii) the need for new estimation methods in areas affected by low to moderate burn severities, even for relatively homogeneous forests.

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