Bayesian estimation method

2009 ◽  
pp. 261-270
Author(s):  
John M. Lewis ◽  
S. Lakshmivarahan ◽  
Sudarshan Dhall
Keyword(s):  
Bayesian Estimation ◽  
Estimation Method

Estimation of Failure Probability and its Applications in Reliability Data Analysis

2010 ◽  
Vol 118-120 ◽  
pp. 601-605
Author(s):  
Han Ming
Keyword(s):  
Parameter Estimation ◽  
Data Analysis ◽  
Bayesian Estimation ◽  
Failure Probability ◽  
Evaluation Method ◽  
Estimation Method ◽  
New Method ◽  
Reliability Parameter ◽  
Hierarchical Bayesian Estimation ◽  
Definition Of

Evaluation method of reliability parameter estimation needs to be improved effectively with the advance of science and technology. This paper develops a new method of parameter estimation, which is named E-Bayesian estimation method. In the case one hyper-parameter, the definition of E-Bayesian estimation of the failure probability is provided, moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation, and the property of E-Bayesian estimation of the failure probability are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.

scholarly journals Comparison between the maximum likelihood and the bayesian estimation methods for logistic regression model (case study: risk of low birth weight in Indonesia)

2021 ◽  
Vol 2106 (1) ◽  
pp. 012001
Author(s):  
P R Sihombing ◽  
S R Rohimah ◽  
A Kurnia
Keyword(s):  
Logistic Regression ◽  
Birth Weight ◽  
Maximum Likelihood ◽  
Low Birth Weight ◽  
Regression Model ◽  
Bayesian Estimation ◽  
Logistic Regression Model ◽  
Estimation Method ◽  
Estimation Methods ◽  
Model Case

Abstract This study aims to compare the efficacy of logistic regression model for identifying the risk factors of low-birth-weight babies in Indonesia using the maximum likelihood estimation (MLE)and the Bayesian estimation methods. The data used in this study is secondary data derived from the 2017 Indonesian Demographic Health Survey with a total sample of 16,344 newborn babies. Selection of the best logistic regression model was based on the smaller Bayesian Schwartz Information Criterion (BIC) value. The logistic regression model with the Bayesian estimation method has a smaller BIC value than the MLE method. Twin births, baby girl, maternal age at risk, birth spacing that is too close, iron deficiency, low education, low economy, inadequate drinking water sources have provided a higher risk of low-birth-weight incidence.

scholarly journals Bayesian Estimation of Potential Performance Improvement Elicited by Robot-Guided Training

2021 ◽  
Vol 15 ◽  
Author(s):  
Asuka Takai ◽  
Giuseppe Lisi ◽  
Tomoyuki Noda ◽  
Tatsuya Teramae ◽  
Hiroshi Imamizu ◽  
...  
Keyword(s):  
Bayesian Estimation ◽  
Motor Performance ◽  
Hand Movement ◽  
Tracking Error ◽  
Estimation Method ◽  
Training Procedure ◽  
Movement Training ◽  
Movement Performance ◽  
Human Motor ◽  
Initial Movement

Improving human motor performance via physical guidance by an assist robot device is a major field of interest of the society in many different contexts, such as rehabilitation and sports training. In this study, we propose a Bayesian estimation method to predict whether motor performance of a user can be improved or not by the robot guidance from the user’s initial skill level. We designed a robot-guided motor training procedure in which subjects were asked to generate a desired circular hand movement. We then evaluated the tracking error between the desired and actual subject’s hand movement. Results showed that we were able to predict whether a novel user can reduce the tracking error after the robot-guided training from the user’s initial movement performance by checking whether the initial error was larger than a certain threshold, where the threshold was derived by using the proposed Bayesian estimation method. Our proposed approach can potentially help users to decide if they should try a robot-guided training or not without conducting the time-consuming robot-guided movement training.

scholarly journals Deriving Atmospheric Temperature of the Tropopause Region–Upper Troposphere by Combining Information from GPS Radio Occultation Refractivity and High-Spectral-Resolution Infrared Radiance Measurements

2008 ◽  
Vol 47 (9) ◽  
pp. 2300-2310 ◽  
Author(s):  
Eva E. Borbas ◽  
W. Paul Menzel ◽  
Elisabeth Weisz ◽  
Dezso Devenyi
Keyword(s):  
Bayesian Estimation ◽  
Spectral Resolution ◽  
Radio Occultation ◽  
Estimation Method ◽  
Principal Component ◽  
Atmospheric Temperature ◽  
High Spectral Resolution ◽  
Statistical Regression ◽  
Infrared Radiance ◽  
Tropopause Region

Abstract Global positioning system radio occultation (GPS/RO) measurements from the Challenging Minisatellite Payload (CHAMP) and Satelite de Aplicaciones Cientificas-C (SAC-C) satellites are used to improve tropospheric profile retrievals derived from the Aqua platform high-spectral-resolution Atmospheric Infrared Sounder (AIRS) and broadband Advanced Microwave Sounding Unit (AMSU) measurements under clear-sky conditions. This paper compares temperature retrievals from combined AIRS, AMSU, and CHAMP/SAC-C measurements using different techniques: 1) a principal component statistical regression using coefficients established between real (and in a few cases calculated) measurements and radiosonde atmospheric profiles; and 2) a Bayesian estimation method applied to AIRS plus AMSU temperature retrievals and GPS/RO temperature profiles. The Bayesian estimation method was also applied to GPS/RO data and the AIRS Science Team operational level-2 (version 4.0) temperature products for comparison. In this study, including GPS/RO data in the tropopause region produces the largest improvement in AIRS–AMSU temperature retrievals—about 0.5 K between 100 and 300 hPa. GPS/RO data are found to provide valuable upper-tropospheric information that improves the profile retrievals from AIRS and AMSU.

Estimation of Failure Rate and its Applications in the Case of Zero-Failure Data

2014 ◽  
Vol 945-949 ◽  
pp. 1046-1049
Author(s):  
Ming Han
Keyword(s):  
Bayesian Estimation ◽  
Failure Rate ◽  
Estimation Method ◽  
New Method ◽  
Hierarchical Bayesian ◽  
Failure Data ◽  
Hierarchical Bayesian Estimation ◽  
Definition Of

This paper introduces a new method, named E-Bayesian estimation method, to estimate failure rate in zero-failure data. The definition of E-Bayesian estimation of the failure rate is given, based on the definition, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation of the failure rate were provided, and properties of the E-Bayesian estimation, i. e. relations between E-Bayesian estimation and hierarchical Bayesian estimation, was discussed. Calculations were performed on practical problems, showing that the proposed new method is feasible and easy to operate.

Simultaneous Ivabradine Parent-Metabolite PBPK/PD Modelling Using a Bayesian Estimation Method

2020 ◽  
Vol 22 (6) ◽  
Author(s):  
Jennifer Lang ◽  
Ludwig Vincent ◽  
Marylore Chenel ◽  
Kayode Ogungbenro ◽  
Aleksandra Galetin
Keyword(s):  
Bayesian Estimation ◽  
Estimation Method

A critical test to disentangle the role of overshooting and rotation in stars

2018 ◽  
Vol 14 (S343) ◽  
pp. 375-376
Author(s):  
G. Costa ◽  
L. Girardi ◽  
A. Bressan ◽  
P. Marigo ◽  
Y. Chen ◽  
...  
Keyword(s):  
Bayesian Estimation ◽  
Massive Stars ◽  
Estimation Method ◽  
Eclipsing Binaries ◽  
Evolutionary Models ◽  
Critical Test ◽  
Rotation Rates ◽  
Reasonable Explanation ◽  
Convective Core

AbstractWe study the mixing in low-intermediate massive stars using eclipsing binaries. We compute stellar evolutionary models with a varying convective core overshooting parameter and different rotation rates. Using a Bayesian estimation method, we found that the coexistence of the two phenomena may be a reasonable explanation of the observed extra-mixing.

scholarly journals A Novel Robust Model Predictive Controller for Aerospace Three-Phase PWM Rectifiers

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2490 ◽  
Author(s):  
Tao Lei ◽  
Weiwei Tan ◽  
Guangsi Chen ◽  
Delin Kong
Keyword(s):  
Power System ◽  
Bayesian Estimation ◽  
Estimation Method ◽  
Parameters Estimation ◽  
Least Square ◽  
Estimation Methods ◽  
Control Performance ◽  
Least Square Estimation ◽  
Three Phase ◽  
Pwm Rectifiers

This paper presents a novel Model Predictive Direct Power Control (MPDPC) approach for the pulse width modulation (PWM) rectifiers in the Aircraft Alternating Current Variable Frequency (ACVF) power system. The control performance of rectifiers may be largely affected by variations in the AC side impedance, especially for systems with limited power volume system. A novel idea for estimating the impedance variation based on the Bayesian estimation, using an algorithm embedded in MPDPC is presented in this paper. The input filter inductance and its equivalent series resistance (ESR) of PWM rectifiers are estimated in this algorithm by measuring the input current and input voltage in each cycle with the probability Bayesian estimation theory. This novel estimation method can overcome the shortcomings of traditional data based estimation methods such as least square estimation (LSE), which achieves poor estimation results with the small samples data set. In ACVF systems, the effect on the parameters estimation accuracy caused by the number of sampling points in one cycle is also analyzed in detail by simulation. The validity of this method is verified by the digital and Hard-in-loop simulation compared with other estimation methods such as the least square estimation method. The experimental testing results show that the proposed estimation algorithm can improve the robustness and the control performance of the MPDPC under the condition of the uncertainty of the AC side parameters of the three-phase PWM rectifiers in aircraft electrical power system.

Estimation of Failure Rate and its Applications

2013 ◽  
Vol 756-759 ◽  
pp. 3149-3152
Author(s):  
Ming Han
Keyword(s):  
Parameter Estimation ◽  
Bayesian Estimation ◽  
Failure Rate ◽  
Estimation Method ◽  
Hierarchical Bayesian ◽  
Parameter Estimation Method ◽  
Hierarchical Bayesian Estimation

This paper introduces a new parameter estimation method, E-Bayesian estimation method, to estimate failure rate. The definition, properties, E-Bayesian estimation and hierarchical Bayesian estimation of failure rate are given. A example is also discussed. Through the example the efficiency and easiness of operation of this method are commended.

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