scholarly journals Improved log-Gaussian approximation for over-dispersed Poisson regression: Application to spatial analysis of COVID-19

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0260836
Author(s):  
Daisuke Murakami ◽  
Tomoko Matsui
Keyword(s):  
Closed Form ◽  
Poisson Regression ◽  
Gaussian Approximation ◽  
Estimation Error ◽  
Open Data ◽  
Identification Problem ◽  
Small Samples ◽  
Estimation Accuracy ◽  
Monte Carlo Experiments ◽  
Additive Mixed Models

In the era of open data, Poisson and other count regression models are increasingly important. Still, conventional Poisson regression has remaining issues in terms of identifiability and computational efficiency. Especially, due to an identification problem, Poisson regression can be unstable for small samples with many zeros. Provided this, we develop a closed-form inference for an over-dispersed Poisson regression including Poisson additive mixed models. The approach is derived via mode-based log-Gaussian approximation. The resulting method is fast, practical, and free from the identification problem. Monte Carlo experiments demonstrate that the estimation error of the proposed method is a considerably smaller estimation error than the closed-form alternatives and as small as the usual Poisson regressions. For counts with many zeros, our approximation has better estimation accuracy than conventional Poisson regression. We obtained similar results in the case of Poisson additive mixed modeling considering spatial or group effects. The developed method was applied for analyzing COVID-19 data in Japan. This result suggests that influences of pedestrian density, age, and other factors on the number of cases change over periods.

scholarly journals Numerical Comparisons Between Bayesian and Frequentist Low-Rank Matrix Completion: Estimation Accuracy and Uncertainty Quantification

2021 ◽  
Author(s):  
The Tien Mai
Keyword(s):  
Confidence Intervals ◽  
Estimation Error ◽  
Matrix Completion ◽  
Low Rank ◽  
Small Samples ◽  
Estimation Accuracy ◽  
Bayesian Approaches ◽  
Rank Matrix ◽  
Low Rank Matrix Completion ◽  
Low Rank Matrix

In this paper we perform numerous numerical studies for the problem of low-rank matrix completion. We compare the Bayesian approaches and a recently introduced de-biased estimator which provides a useful way to build confidence intervals of interest. From a theoretical viewpoint, the de-biased estimator comes with a sharp minimax-optimal rate of estimation error whereas the Bayesian approach reaches this rate with an additional logarithmic factor. Our simulation studies show originally interesting results that the de-biased estimator is just as good as the Bayesian estimators. Moreover, Bayesian approaches are much more stable and can outperform the de-biased estimator in the case of small samples. However, we also find that the length of the confidence intervals revealed by the de-biased estimator for an entry is absolutely shorter than the length of the considered credible interval. These suggest further theoretical studies on the estimation error and the concentration for Bayesian methods as they are being quite limited up to present.

scholarly journals Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

2009 ◽  
Vol 132 (3) ◽  
Author(s):  
Donald L. Simon ◽  
Sanjay Garg
Keyword(s):  
Kalman Filter ◽  
Estimation Error ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Performance Estimation ◽  
Experimental Simulation ◽  
Tuning Parameter ◽  
Estimation Accuracy ◽  
On Line

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multivariable iterative search routine that seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared with the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy.

Assessment of 2D ultrasound fluid volume estimation accuracy in different shaped objects: an in vitro study

2019 ◽  
Vol 61 (2) ◽  
pp. 253-259
Author(s):  
Iroshani Kodikara ◽  
Iroshini Abeysekara ◽  
Dhanusha Gamage ◽  
Isurani Ilayperuma
Keyword(s):  
Estimation Error ◽  
In Vitro Study ◽  
High Accuracy ◽  
Volume Estimation ◽  
Estimation Accuracy ◽  
Rater Agreement ◽  
Actual Volume ◽  
2D Ultrasound ◽  
One Way Anova

Background Volume estimation of organs using two-dimensional (2D) ultrasonography is frequently warranted. Considering the influence of estimated volume on patient management, maintenance of its high accuracy is empirical. However, data are scarce regarding the accuracy of estimated volume of non-globular shaped objects of different volumes. Purpose To evaluate the volume estimation accuracy of different shaped and sized objects using high-end 2D ultrasound scanners. Material and Methods Globular (n=5); non-globular elongated (n=5), and non-globular near-spherical shaped (n=4) hollow plastic objects were scanned to estimate the volumes; actual volumes were compared with estimated volumes. T-test and one-way ANOVA were used to compare means; P<0.05 was considered significant. Results The actual volumes of the objects were in the range of 10–445 mL; estimated volumes ranged from 6.4–425 mL ( P=0.067). The estimated volume was lower than the actual volume; such volume underestimation was marked for non-globular elongated objects. Regardless of the scanner, the highest volume estimation error was for non-globular elongated objects (<40%) followed by non-globular near-spherical shaped objects (<23.88%); the lowest was for globular objects (<3.6%). Irrespective of the shape or the volume of the object, volume estimation difference among the scanners was not significant: globular (F=0.430, P=0.66); non-globular elongated (F=3.69, P=0.064); and non-globular near-spherical (F=4.00, P=0.06). A good inter-rater agreement (R=0.99, P<0.001) and a good correlation between actual versus estimated volumes (R=0.98, P<0.001) were noted. Conclusion The 2D ultrasonography can be recommended for volume estimation purposes of different shaped and different sized objects, regardless the type of the high-end scanner used.

Analytical Model for High–Level Area Estimation of FPGA Design

2016 ◽  
Vol 7 (2) ◽  
pp. 35-44
Author(s):  
Rachna Singh ◽  
Arvind Rajawat
Keyword(s):  
Early Stage ◽  
Estimation Error ◽  
Research Work ◽  
Performance Estimation ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Fpga Design ◽  
Estimation Model ◽  
Area Estimation ◽  
High Level

FPGAs have been used as a target platform because they have increasingly interesting in system design and due to the rapid technological progress ever larger devices are commercially affordable. These trends make FPGAs an alternative in application areas where extensive data processing plays an important role. Consequently, the desire emerges for early performance estimation in order to quantify the FPGA approach. A mathematical model has been presented that estimates the maximum number of LUTs consumed by the hardware synthesized for different FPGAs using LLVM.. The motivation behind this research work is to design an area modeling approach for FPGA based implementation at an early stage of design. The equation based area estimation model permits immediate and accurate estimation of resources. Two important criteria used to judge the quality of the results were estimation accuracy and runtime. Experimental results show that estimation error is in the range of 1.33% to 7.26% for Spartan 3E, 1.6% to 5.63% for Virtex-2pro and 2.3% to 6.02% for Virtex-5.

Hierarchical Estimator of Dual Clutch Torques for a Power-Split Hybrid Electric Vehicle

2019 ◽  
Author(s):  
Jianwu Zhang ◽  
Defeng Xu
Keyword(s):  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Estimation Error ◽  
Transient State ◽  
Estimation Accuracy ◽  
Unknown Input ◽  
Unknown Input Observer ◽  
Reduced Order ◽  
Power Split ◽  
Reduced Order Observer

Abstract For fast drive mode transitions by shifting clutches equipped in the dedicated compound power-split hybrid transmission, correct estimations of pressure and torque of the clutches are crucial for control strategies. A hierarchical estimator is proposed herein for individual estimation of the clutch torques, consisting of not only the reference layer containing the unknown input observer of vehicle resistance and the reduced-order observer of drive shaft torque, but also the estimation layer combining the unknown input observer with the reduced-order observer. The estimator is implemented to strike a balance between estimation accuracy in the steady state and real time response in the transient state. For validation of the estimator, simulations and real car tests are carried out in specific drive conditions. By numerical results, it’s demonstrated that excellent predictive abilities are found including reasonably small estimation error and adaptive capability and, as a result, shift to shift induced driveline oscillations and vehicle jerks are reduced significantly.

Practical Site-Specific Earthquake Early Warning Application

2009 ◽  
Vol 4 (4) ◽  
pp. 579-587 ◽  
Author(s):  
Katsuhisa Kanda ◽  
◽  
Tadashi Nasu ◽  
Masamitsu Miyamura
Keyword(s):  
Early Warning ◽  
Estimation Error ◽  
Seismic Intensity ◽  
Earthquake Early Warning ◽  
P Wave ◽  
Japan Meteorological Agency ◽  
Estimation Accuracy ◽  
Intensity Estimation ◽  
Site Specific ◽  
Wide Range

Real-time hazard mitigation we have developed using earthquake early warning (EEW) (1) enhances seismic intensity estimation accuracy and (2) extends the interval between when an EEW is issued and when strong tremors arrive. We accomplished the first point (enhancing seismic intensity estimation) by reducing estimation error to less than that commonly used based on an attenuation relationship and soil amplification factor by considering source-location and wave propagation path differences based on site-specific empiricism. We accomplished the second point (shortening the time between warnings and when tremors arrive) using a high-speed, reliable communication network for receiving EEW information from the Japan Meteorological Agency (JMA) and quickly transmitting warning signals to users. In areas close to quake epicenters, however, warnings may not arrive before the arrival of strong ground motions. The on-site warning system we developed uses P-wave pickup sensors that detect P-wave arrival at a site and predict seismic intensity of subsequent S-waves. We confirmed the on-site warning prototype’s feasibility based on numerical simulation and observation. We also developed an integration server for combining on-site warnings with JMA information to be applied to earthquakes over a wide range of distances. We installed a practical prototype at a construction site near the 2008 Iwate-Miyagi Inland Earthquake epicenter to measure its aftershocks because JMA EEW information was too late to use against the main shock. We obtained good aftershock results, confirming the prototype’s applicability and accuracy. Integration server combination logic was developed for manufacturing sites requiring highly robust, reliable control.

Rekursive oder nicht-rekursive Modelle? / Testing for non-recursiveness in causal modelling

1975 ◽  
Vol 4 (3) ◽  
Author(s):  
Christof Ammermann ◽  
Peter Gluchowski ◽  
Peter Schmidt
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Error Term ◽  
Causal Model ◽  
Identification Problem ◽  
Testing Procedure ◽  
Small Samples ◽  
Theory Construction ◽  
Causal Modelling ◽  
Oder Nicht

AbstractThe paper discusses a stubborn problem of theory construction: deciding between recursive and non- recursive variants of a causal model by testing them against empirical data. After pointing out the consequences of a correlation between an exogeneous variable and the error term of an endogeneous variable as well as certain aspects of the identification problem we show for the asymptotic case (n → ∞) that a test is possible if the correlation between the exogeneous and the error term is in fact zero. Following this we present the results of a Monte-Carlo simulation investigating the robustness of the proposed test when applied to small samples. Finally we suggest conclusions of this testing procedure for empirical research.

scholarly journals Fractional baud-length coding

2011 ◽  
Vol 29 (6) ◽  
pp. 1189-1196
Author(s):  
J. Vierinen
Keyword(s):  
Estimation Error ◽  
Estimation Accuracy ◽  
Target Range ◽  
Estimation Errors ◽  
Range Resolution ◽  
Error Covariance ◽  
Novel Approach ◽  
Amplitude Estimation ◽  
Radar Measurements ◽  
Low Altitude

Abstract. We present a novel approach for modulating radar transmissions in order to improve target range and Doppler estimation accuracy. This is achieved by using non-uniform baud lengths. With this method it is possible to increase sub-baud range-resolution of phase coded radar measurements while maintaining a narrow transmission bandwidth. We first derive target backscatter amplitude estimation error covariance matrix for arbitrary targets when estimating backscatter in amplitude domain. We define target optimality and discuss different search strategies that can be used to find well performing transmission envelopes. We give several simulated examples of the method showing that fractional baud-length coding results in smaller estimation errors than conventional uniform baud length transmission codes when estimating the target backscatter amplitude at sub-baud range resolution. We also demonstrate the method in practice by analyzing the range resolved power of a low-altitude meteor trail echo that was measured using a fractional baud-length experiment with the EISCAT UHF system.

scholarly journals Robust State Estimation of Induction Motor using Desensitized Rank Kalman Filter

2020 ◽  
Author(s):  
Tai-shan Lou ◽  
Dong-xuan Han ◽  
Xiao-liang Yang ◽  
Su-xia Jiang
Keyword(s):  
State Estimation ◽  
Induction Motor ◽  
Kalman Filtering ◽  
Sampling Methods ◽  
Estimation Error ◽  
Sensitivity Function ◽  
Estimation Accuracy ◽  
Uncertain Parameters ◽  
Excellent Performance ◽  
Deterministic Sampling

To improve the state estimation accuracy of nonlinear induction motor with uncertain parameters, a robust desensitized rank Kalman filtering (DRKF) is proposed to reduce state estimation error sensitivities to uncertain parameters. A new sensitivity function is defined, and a novel desensitized cost function for the deterministic sampling methods is designed to obtain an optimal gain matrix. The sensitivity propagation is summarized for deterministic sampling methods. Based on the rank sample rule, the sensitivity propagation method is given, and the DRKF algorithm is derived. Two dynamic behaviors of the induction motor with two uncertain stator and rotor resistances are simulated to demonstrate that the proposed DRKF has an excellent performance.

scholarly journals Evaluation for hypocenter estimation error in the southwestern Kuril trench using Japan and Russia joint seismic data

2020 ◽  
Author(s):  
Masayoshi Ichiyanagi ◽  
Mikhaylov Valentin ◽  
Dmitry Kostylev ◽  
Yuri Levin ◽  
Hiroaki Takahashi
Keyword(s):  
Real Time ◽  
Seismic Data ◽  
Estimation Error ◽  
Tsunami Warning ◽  
Disaster Mitigation ◽  
Border Zone ◽  
Japan Meteorological Agency ◽  
Estimation Accuracy ◽  
Waveform Data ◽  
Kuril Trench

Abstract The southwestern Kuril trench is seismically active due to the subduction of the Pacific plate. Great earthquakes in this zone have frequently induced fatal disasters. Seismic monitoring and hypocenter catalogues provide fundamental information on earthquake occurrence and disaster mitigation. Real-time hypocenter and magnitude estimates are extremely crucial data for tsunami warning systems. However, this region is located in the international border zone between Japan and Russia. The Japan Meteorological Agency and Russian Academy of Sciences have routinely determined hypocenters and issued earthquake information independently. Waveform data have not yet been exchanged internationally in real time. Here, we evaluated how a hypothetical Japan-Russia joint seismic network could potentially improve the hypocenter estimation accuracy. Experiments using numerical and observed data indicated that the joint network extended the distance over which hypocenters can be accurately determined over 100 km eastward compared to the Japan network only. This fact suggests that joint seismic data have the potential to improve the hypocenter accuracy in this region, which would provide improved performance in gathering disaster information at the moment of a tsunami warning.

Sign in / Sign up

Export Citation Format

Share Document