Parameter Estimation: Definition and Sampling Design

2017 ◽  
pp. 53-78
Author(s):  
Gerard Sanz ◽  
Ramon Pérez
Keyword(s):  
Parameter Estimation ◽  
Sampling Design

Sampling design schemes for distributed parameter estimation networks

2016 ◽  
Vol 22 (1) ◽  
pp. 62
Author(s):  
Ming Fong Hsu ◽  
Tsang Yi Wang ◽  
Chao Tang Yu ◽  
Tsai Cheng Wu
Keyword(s):  
Parameter Estimation ◽  
Sampling Design ◽  
Distributed Parameter ◽  
Distributed Parameter Estimation

scholarly journals A Coupled Sampling Design for Parameter Estimation in Microalgae Growth Experiment: Maximizing the Benefits of Uniform and Non-Uniform Sampling

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 2996
Author(s):  
Hao Li ◽  
Enze Zhang
Keyword(s):  
Parameter Estimation ◽  
Confidence Interval ◽  
Prior Knowledge ◽  
Sampling Design ◽  
Parameter Estimates ◽  
Parameter Distribution ◽  
Model Parameters ◽  
Uniform Sampling ◽  
Sampling Points ◽  
Non Uniform Sampling

As an important primary producer in aquatic ecosystems, the various parameters within the mathematical models are used to describe the growth of microalgae and need to be estimated by carefully designed experiments. Non-uniform sampling has proved to generate a deliberately optimized sampling temporal schedule that can benefit parameter estimation. However, the current non-uniform sampling method depends on prior knowledge of the nominal values of the model parameters. It also largely ignores the uncertainty associated with the nominal values, thus inducing unacceptable parameter estimates. This study focuses on the uncertainty problem and describes a new sampling design that couples the traditional uniform and non-uniform sampling schedules to benefit from the merits of both methods. Based on D-optimal design, we first derive the non-uniform optimal sampling points by maximizing the determinant of the Fisher information matrix. Then the confidence interval around the non-uniform sampling points is determined by Monte Carlo simulations based on the prior knowledge of parameter distribution. Finally, we wrap the non-uniform sampling points with the uniform sampling points within the confidence interval to obtain the ultimate optimal experimental design. Scenedesmus obliquus, whose growth curve follows a four-parameter model, was used as a case study. Compared with the traditional sampling design, the simulation results show that our proposed coupled sampling schedule can partly eliminate the uncertainty in parameter estimates caused by fixed systematic errors in observations. Our coupled sampling can also retain some advantages belonging to non-uniform sampling, in exploiting information maximization and managing the cost of sampling.

scholarly journals From the Help Desk: It's all about the Sampling

2002 ◽  
Vol 2 (2) ◽  
pp. 190-201 ◽  
Author(s):  
Allen McDowell ◽  
Jeff Pitblado
Keyword(s):  
Monte Carlo ◽  
Parameter Estimation ◽  
Monte Carlo Simulations ◽  
Survey Data ◽  
Sampling Design ◽  
Hypothesis Tests ◽  
Complex Survey ◽  
Help Desk ◽  
Simple Hypothesis ◽  
Survey Designs

Effective estimation and inference, when the data are collected using complex survey designs, requires estimators that fully account for the sampling design. This article explores, by means of Monte Carlo simulations of the power of simple hypothesis tests, the consequences of parameter estimation and inference when naive estimators are employed with survey data.

Weighted Combination of Prior and Sample Information and Parameter Estimation

Optimization ◽  
1976 ◽  
Vol 7 (5) ◽  
pp. 665-672
Author(s):  
H. Burke ◽  
C. Hennig ◽  
W H. Schmidt
Keyword(s):  
Parameter Estimation ◽  
Sample Information ◽  
Weighted Combination
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