On estimation efficiency of the central mean subspace

2013 ◽  
Vol 76 (5) ◽  
pp. 885-901 ◽  
Author(s):  
Yanyuan Ma ◽  
Liping Zhu
Keyword(s):  
Estimation Efficiency ◽  
Central Mean Subspace

scholarly journals Measuring spatial price differentials at the basic heading level: a comparison of stochastic index number methods

2021 ◽  
Author(s):  
Sebastian Weinand
Keyword(s):  
Price Level ◽  
Consumer Price Index ◽  
Index Number ◽  
Price Data ◽  
Estimation Efficiency ◽  
Spatial Price ◽  
Price Comparisons ◽  
High Degree ◽  
The Impact

AbstractSpatial price comparisons rely to a high degree on the quality of the underlying price data that are collected within or across countries. Below the basic heading level, these price data often exhibit large gaps. Therefore, stochastic index number methods like the Country–Product–Dummy (CPD) method and the Gini–Eltetö–Köves–Szulc (GEKS) method are utilised for the aggregation of the price data into higher-level indices. Although the two index number methods produce differing price level estimates when prices are missing, the present paper demonstrates that both can be derived from exactly the same stochastic model. For a specific case of missing prices, it is shown that the formula underlying these price level estimates differs between the two methods only in weighting. The impact of missing prices on the efficiency of the price level estimates is analysed in two simulation studies. It can be shown that the CPD method slightly outperforms the GEKS method. Using micro data of Germany’s Consumer Price Index, it can be observed that more narrowly defined products improve estimation efficiency.

Relative Pose Estimation under Monocular Vision in Rendezvous and Docking

2013 ◽  
Vol 433-435 ◽  
pp. 799-805 ◽  
Author(s):  
Hui Pan ◽  
Jian Yu Huang ◽  
Shi Yin Qin
Keyword(s):  
Estimation Algorithm ◽  
Monocular Vision ◽  
Estimation Accuracy ◽  
Estimation Efficiency ◽  
Autonomous Rendezvous ◽  
Space Programs ◽  
Efficiency Estimation ◽  
Relative Pose ◽  
Rendezvous And Docking ◽  
Model Approach

Autonomous rendezvous and docking (ARD) plays a very important role in planned space programs such as on-orbit construction and assembly, refueling of satellites, repairing or rescuing failed satellites, active removal of space debris, autonomous re-supply and crew exchange of space stations, and so on. However,the success of ARD rests with the estimation accuracy and efficiency of relative pose among various spacecraft in rendezvous and docking. In this paper, a high accuracy and efficiency estimation algorithm of relative pose of cooperative space targets is presented based on monocular vision imaging, in which a modified gravity model approach and multiple targets tracking methods are employed to improve the accuracy of feature extraction and enhance the estimation efficiency, moreover the Levenberg-Marquardt method (LMM) is used to achieve a well global convergence. The comprehensive experiment results demonstrate its outstanding predominance in estimation accuracy and efficiency.

Deconvolution of Event-Related fMRI Responses in Fast-Rate Experimental Designs: Tracking Amplitude Variations

2000 ◽  
Vol 12 (supplement 2) ◽  
pp. 76-89 ◽  
Author(s):  
Hermann Hinrichs ◽  
Michael Scholz ◽  
Claus Tempelmann ◽  
Martin G. Woldorff ◽  
Anders M. Dale ◽  
...  
Keyword(s):  
Temporal Variations ◽  
Experimental Designs ◽  
Data Sets ◽  
Statistical Efficiency ◽  
Hemodynamic Response Function ◽  
Detection Rates ◽  
Visual Spatial ◽  
Estimation Efficiency ◽  
Recent Developments ◽  
Noise Covariance

Recent developments towards event-related functional magnetic resonance imaging has greatly extended the range of experimental designs. If the events occur in rapid succession, the corresponding time-locked responses overlap significantly and need to be deconvolved in order to separate the contributions of different events. Here we present a deconvolution approach, which is especially aimed at the analysis of fMRI data where sequence- or context-related responses are expected. For this purpose, we make the assumption of a hemodynamic response function (HDR) with constant yet not predefined shape but with possibly variable amplitudes. This approach reduces the number of variables to be estimated but still keeps the solutions flexible with respect to the shape. Consequently, statistical efficiency is improved. Temporal variations of the HDR strength are directly indicated by the amplitudes derived by the algorithm. Both the estimation efficiency and statistical inference are further supported by an improved estimation of the noise covariance. Using synthesized data sets, both differently shaped HDRs and varying amplitude factors were correctly identified. The gain in statistical sensitivity led to improved ratios of false- and true-positive detection rates for synthetic activations in these data. In an event-related fMRI experiment with a human subject, different HDR amplitudes could be derived corresponding to stimulation at different visual stimulus contrasts. Finally, in a visual spatial attention experiment we obtained different fMRI response amplitudes depending on the sequences of attention conditions.

scholarly journals Improving Woody Biomass Estimation Efficiency Using Double Sampling

Forests ◽  
2012 ◽  
Vol 3 (2) ◽  
pp. 179-189
Author(s):  
David L. Parrott ◽  
John M. Lhotka ◽  
Songlin Fei ◽  
B. Scott Shouse
Keyword(s):  
Woody Biomass ◽  
Biomass Estimation ◽  
Double Sampling ◽  
Estimation Efficiency
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