Results 61 to 70 of about 22,359,362 (203)

Unbiased covariance estimation with interpolated data [PDF]

We study covariance estimation when compelled to use evenly spaced data which have already been manipulated by previous-tick interpolation. We propose an un- biased covariance estimator, which is designed to correct for the two biases arising because of ...
Taro Kanatani, Roberto Reno'
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Inverse problems in covariate data analysis

Frontiers in Applied Mathematics and Statistics
The fact that Pearson's correlation coefficient and effect size are perspective functions of covariance parameters demonstrates that how covariance is defined is one of the most important issues in data analysis.
Stanley Luck
doaj   +1 more source

Portfolio risk measurement: the estimation of the covariance of stock returns [PDF]

A covariance matrix of asset returns plays an important role in modern portfolio analysis and risk management. Despite the recent interests in improving the estimation of a return covariance matrix, there remain many areas for further investigation. This
Liu, Lan
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The Performance Analysis Based on SAR Sample Covariance Matrix

Sensors, 2012
Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a ...
Esra Erten
doaj   +1 more source

"Maximum Covariance Di erence Test for Equality of Two Covariance Matrices" [PDF]

We propose a test of equality of two covariance matrices based on the maximum standardized di erence of scalar covariances of two sample covariance matrices.We derive the tail probability of the asymptotic null distribution of the test statistic by the ...
Akimichi Takemura, Satoshi Kuriki
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Development and verification of covariance data generation module in NECP-Atlas

He jishu
BackgroundThe quantification of uncertainty has become a common requirement in reactor physics analysis whilst the covariance data of nuclear data serves as the foundational data for conducting uncertainty quantification.PurposeThis study aims to develop
HUANG Yihan, ZU Tiejun, CAO Liangzhi, WU Hongchun   +3 more
doaj   +1 more source

Application of student's t-test, analysis of variance, and covariance

Annals of Cardiac Anaesthesia, 2019
Student's t test (t test), analysis of variance (ANOVA), and analysis of covariance (ANCOVA) are statistical methods used in the testing of hypothesis for comparison of means between the groups.
Prabhaker Mishra, Uttam Singh, Chandra M Pandey, Priyadarshni Mishra, Gaurav Pandey   +4 more
doaj   +1 more source

General balance, combination of information and the analysis of covariance

, 1992
A resume is given of the conditions and underlying theory for general balance of an experimental design, paying particular attention to their relationships to the usual linear models for analysis of variance and the marginality relationships between the ...
Tobias, R. D., Payne, R. W.
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Microdosimetry of diagnostic X-rays: applications of the variance-covariance method. [PDF]

, 1992
Microdosimetric measurements in beams of diagnostic X rays (between 30 and 125 kV) have been performed. In these pulsed radiation fields, microdosimetric measurements are possible only by application of the variance-covariance technique.
Kellerer, Albrecht M., Chen, J., Kellerer, A.M., Roos, H.   +3 more
core   +1 more source

A new class of nonseparable space-time covariance models [PDF]

, 2008
The aim of this work is to construct nonseparable, stationary covariance functions for processes that vary continuously in space and time. Stochastic modeling of phenomena over space and time is important in many areas of applications such as ...
Fonseca, Thaís C. O., Steel, Mark F. J.
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