Robust Estimation Method Based on Function Model of Successive Approximation

2021 ◽  
Author(s):  
Ye Xiaoming
Keyword(s):  
Robust Estimation ◽  
Physical Mechanism ◽  
Estimation Method ◽  
Theoretical Method ◽  
Discrete Distributions ◽  
Function Model ◽  
Repeated Observation ◽  
Least Squares Adjustment ◽  
Approximate Function ◽  
True Values

Abstract In measurement practice, the residuals in least squares adjustment usually show various abnormal discrete distributions, including outliers, which is not conducive to the optimization of final measured values. Starting with the physical mechanism of dispersion and outlier of repeated observation errors, this paper puts forward the error correction idea of using the approximate function model of error to approach the actual function model of error step by step, gives a new theoretical method to optimize the final measured values, and proves the effectiveness of the algorithm by the ability of responding to the true values. This new idea is expected to be the ultimate answer of robust estimation theory.

scholarly journals A General and Robust Estimation Method for the Case-Time-Control Design

2019 ◽  
Vol 49 (1) ◽  
pp. 349-365
Author(s):  
Arvid Sjölander ◽  
Yang Ning
Keyword(s):  
Robust Estimation ◽  
Arbitrary Number ◽  
Estimation Method ◽  
Control Design ◽  
Time Varying ◽  
Time Control ◽  
Measured Time ◽  
Important Extension ◽  
Time Varying Covariates

The case-time-control design is a tool to control for measured, time-varying covariates that increase montonically in time within each subject while also controlling for all unmeasured covariates that are constant within each subject across time. Until recently, the design was restricted to data with only two timepoints and a single binary covariate, or data with a binary exposure. Sjölander (2017) made an important extension that allows for an arbitrary number of timepoints and covariates and a nonbinary exposure. However, his estimation method requires fairly strong model assumptions, and it may create bias if these assumptions are violated. We propose a novel estimation method for the case-time-control design, which to a large extent relaxes the model assumptions in Sjölander. We show in simulations that this estimation method performs well under a range of scenarios and gives consistent estimates when Sjölander’s estimation does not.

Uncertainty Estimation Method for Windspeed Random Fluctuation Based on it’s Amplitude Modulation Effect

2014 ◽  
Vol 945-949 ◽  
pp. 2801-2805
Author(s):  
Jie Wan ◽  
Zhi Gang Zhao ◽  
Guo Rui Ren ◽  
Cheng Cheng Qiao ◽  
Cheng Rui Lei ◽  
...  
Keyword(s):  
Amplitude Modulation ◽  
Physical Mechanism ◽  
Estimation Method ◽  
Engineering Application ◽  
Uncertainty Estimation ◽  
Residual Error ◽  
Random Fluctuation ◽  
Modulation Effect ◽  
Electric System ◽  
General Statistical

At present, with the development of wind’s energy application and disaster prevention, the windspeed uncertainty must be estimated because of the existing large gap between the requirement of prediction performance and current techniques owing to it’s strong random fluctuation. In this paper, a new method for windspeed uncertainty estimation is proposed on the base of physical mechanism, the inherent amplitude modulation effect in windspeed. According to the the atmosphere motion power spectrum in low-layers, the actual windspeed is usually decomposed into the hourly average windspeed and the turbulent residual error by many researchers. And the turbulent residual error and the turbulent standard deviation is modulated by the hourly average windspeed. Moreover experiments further show that the confidence interval of windspeed random fluctuation uncertainty based on it’s amplitude modulation effect is more rigorous than that obtained by general statistical model. As a result, this uncertainty estimation method has certain physical academic meaning and engineering application value both in the electric system and the other wind domain.

A robust estimation method for topology error identification

1999 ◽  
Vol 14 (4) ◽  
pp. 1469-1476 ◽  
Author(s):  
L. Mili ◽  
G. Steeno ◽  
F. Dobraca ◽  
D. French
Keyword(s):  
Robust Estimation ◽  
Estimation Method ◽  
Error Identification

scholarly journals The Best Robust Estimation Method to Determine Local Surface

2019 ◽  
Vol 7 (4) ◽  
Author(s):  
Łukasz Borowski ◽  
Marek Banaś
Keyword(s):  
Robust Estimation ◽  
Estimation Method ◽  
Local Surface

scholarly journals A New Fuzzy-Cluster-Based Cycle-Slip Detection Method for GPS Single-Frequency Observation

2019 ◽  
Vol 11 (24) ◽  
pp. 2896
Author(s):  
Zongnan Li ◽  
Min Li ◽  
Chuang Shi ◽  
Liang Chen ◽  
Chenlong Deng ◽  
...  
Keyword(s):  
Robust Estimation ◽  
Detection Rate ◽  
Detection Method ◽  
Estimation Method ◽  
Fuzzy Cluster ◽  
Correct Detection ◽  
Single Frequency ◽  
Cycle Slip ◽  
Cycle Slips ◽  
Cycle Slip Detection

The development of low-cost, small, modular receivers and their application in diverse scenarios with complex data quality has increased the requirements of single-frequency carrier-phase data preprocessing in real time. Different methods have been developed, but successful detection is not always ensured. The issue is crucial for high-precision positioning with Global Positioning System (GPS). Aiming at a high detection rate and low false-alarm rate, we propose a new cycle-slip detection method based on fuzzy-cluster. It consists of two steps. The first is identification of the epoch when cycle slips appear using Chi-square test based on time-differenced observations. The second is identification of the satellite which suffers from cycle slips using the fuzzy-cluster algorithm. To verify the performance of the proposed method, we compared it to a current robust method using real single-frequency data with simulated cycle slips. Results indicate that the proposed method outperforms the robust estimation method, with a higher correct-detection rate and lower undetection rate. As the number of satellites simulated with cycle slips increases, the correct-detection rate rapidly decreases from 100% to below 50% with the robust estimation method. While the correct-detection rate using the proposed method is always more than 60%, even if the number of satellites simulated with cycle slips reaches five. In addition, the proposed method always has a lower undetection rate than the robust estimation method. Simulation showed that when the number of satellites with cycle slips exceeds three, the undetection rate increases to more than 30%, reaching ~70% for the robust estimation method and less than 30% for the proposed method.

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