scholarly journals Low-rank approximations for large stationary covariance matrices, as used in the Bayesian and generalized-least-squares analysis of pulsar-timing data

2014 ◽  
Vol 446 (2) ◽  
pp. 1170-1174 ◽  
Author(s):  
Rutger van Haasteren ◽  
Michele Vallisneri
Keyword(s):  
Least Squares ◽  
Generalized Least Squares ◽  
Covariance Matrices ◽  
Low Rank ◽  
Pulsar Timing ◽  
Timing Data ◽  
Low Rank Approximations

Determination of Estimators with Minimum Asymptotic Covariance Matrices

1993 ◽  
Vol 9 (4) ◽  
pp. 633-648 ◽  
Author(s):  
Charles E. Bates ◽  
Halbert White
Keyword(s):  
Least Squares ◽  
Rate Of Convergence ◽  
Asymptotic Variance ◽  
Generalized Least Squares ◽  
Covariance Matrices ◽  
Variance Estimator ◽  
Objective Functions ◽  
Generalized Least Squares Estimator ◽  
Asymptotic Covariance

We give a straightforward condition sufficient for determining the minimum asymptotic variance estimator in certain classes of estimators relevant to econometrics. These classes are relatively broad, as they include extremum estimation with smooth or nonsmooth objective functions; also, the rate of convergence to the asymptotic distribution is not required to be n−½. We present examples illustrating the content of our result. In particular, we apply our result to a class of weighted Huber estimators, and obtain, among other things, analogs of the generalized least-squares estimator for least Lp-estimation, 1 ≤ p < ∞.

scholarly journals A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions

2021 ◽  
Author(s):  
Simone Persiano ◽  
Jose Luis Salinas ◽  
Jery Russell Stedinger ◽  
William H. Farmer ◽  
David Lun ◽  
...  
Keyword(s):  
Least Squares ◽  
Generalized Least Squares ◽  
Least Squares Regression

scholarly journals Ensemble Pulsar Time Study by Pulsar Timing Observations

2004 ◽  
Vol 218 ◽  
pp. 439-440
Author(s):  
Tinggao Yang ◽  
Guangren Ni
Keyword(s):  
Time Scale ◽  
Wavelet Decomposition ◽  
Time Study ◽  
Millisecond Pulsar ◽  
Millisecond Pulsars ◽  
Pulsar Time ◽  
Pulsar Timing ◽  
Timing Data ◽  
Gravitational Wave Background

Long term timing of multiple millisecond pulsars can contribute to the study of an ensemble pulsar time scale PTens. A wavelet decomposition algorithm (WDA) was applied to define a PTens using the available millisecond pulsar timing datA. The PTens obtained from WDA is more stable than those resulting from other algorithms. The Chinese 50 m radio telescope is specially designed for PTens study and detection of gravitational wave background via millisecond pulsars timing observations. A scheme for multiple millisecond pulsar timing and ensemble pulsar time study is discussed in some detail.

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