Bias correction for direct spectral estimation from irregularly sampled data including sampling schemes with correlation

Abstract The prediction and correction of systematic errors in direct spectral estimation from irregularly sampled data taken a stochastic process is investigated. Different sampling schemes are investigated, which lead to such an irregular the observed process. Both kinds considered, with non-equidistant intervals continuous distribution and, on other hand, nominally equidistant missing individual samples yielding discrete intervals. For both distributions intervals, discrete, different rules On one purely random independent times considered. This given only those cases, where occurrence sample at certain time has no influence sequence. excludes any preferred delay or external selection processes, introduce correlations between instances. interdependency thus correlation instances whenever way influences further instances, e.g., recovery after instance, preferences including, jitter source influencing validity samples. A bias-free content goal this investigation.