Systematic sampling with errors in sample locations
MetadataShow full item record
Systematic sampling of points in continuous space is widely used in microscopy and spatial surveys. Classical theory provides asymptotic expressions for the variance of estimators based on systematic sampling as the grid spacing decreases. However, the classical theory assumes that the sample grid is exactly periodic; real physical sampling procedures may introduce errors in the placement of the sample points. This paper studies the effect of errors in sample positioning on the variance of estimators in the case of one-dimensional systematic sampling. First we sketch a general approach to variance analysis using point process methods. We then analyze three different models for the error process, calculate exact expressions for the variances, and derive asymptotic variances. Errors in the placement of sample points can lead to substantial inflation of the variance, dampening of zitterbewegung, that is fluctuation effects, and a slower order of convergence. This suggests that the current practice in some areas of microscopy may be based on over-optimistic predictions of estimator accuracy. © 2010 Biometrika Trust.
Showing items related by title, author, creator and subject.
Modelling the co-occurence of Streptococcus pneumoniae with other bacterial and viral pathogens in the upper respiratory tractJacoby, P.; Watson, K.; Bowman, J.; Taylor, A.; Riley, T.; Smith, D.; Lehmann, Deborah (2007)Go to ScienceDirect® Home Skip Main Navigation Links Brought to you by: The University of Western Australia Library Login: + Register Athens/Institution Login Not Registered? - User Name: Password: ...
Awange, Joseph; Palancz, B.; Lewis, R.; Lovas, T.; Heck, B.; Fukuda, Y. (2016)Traditionally, the least-squares method has been employed as a standard technique for parameter estimation and regression fitting of models to measured points in data sets in many engineering disciplines, geoscience fields ...
Spectral analysis of the Earth’s topographic potential via 2D-DFT: a new data-based degree variance model to degree 90,000Rexer, Moritz; Hirt, Christian (2015)Classical degree variance models (such as Kaula’s rule or the Tscherning-Rapp model) often rely on low-resolution gravity data and so are subject to extrapolation when used to describe the decay of the gravity field at ...