Support Estimation with Sampling Artifacts and Errors

AbstractMotivationThe standard bootstrap method is used throughout science and engineering to perform general-purpose non-parametric resampling and re-estimation. Among the most widely cited and widely used such applications is the phylogenetic bootstrap method, which Felsenstein proposed in 1985 as a means to place statistical confidence intervals on an estimated phylogeny (or estimate “phylogenetic support”). A key simplifying assumption of the bootstrap method is that input data are independent and identically distributed (i.i.d.). However, the i.i.d. assumption is an over-simplification for biomolecular sequence analysis, as Felsenstein noted. Special-purpose fully parametric or semi-parametric methods for phylogenetic support estimation have since been introduced, some of which are intended to address this concern.ResultsIn this study, we introduce a new sequence-aware non-parametric resampling technique, which we refer to as RAWR (“RAndom Walk Resampling”). RAWR consists of random walks that synthesize and extend the standard bootstrap method and the “mirrored inputs” idea of Landan and Graur. We apply RAWR to the task of phylogenetic support estimation. RAWR’s performance is compared to the state of the art using synthetic and empirical data that span a range of dataset sizes and evolutionary divergence. We show that RAWR support estimates offer comparable or typically superior type I and type II error compared to phylogenetic bootstrap support as well as GUIDANCE2, a state-of-the-art purpose-built fully parametric method. Additional simulation study experiments help to clarify practical considerations regarding RAWR support estimation. We conclude with thoughts on future research directions and the untapped potential for sequence-aware non-parametric resampling and re-estimation.AvailabilityData and software are publicly available under open-source software and open data licenses at: https://gitlab.msu.edu/liulab/[email protected]

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Impact of satellite viewing swath width on global and regional aerosol optical thickness statistics and trends

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-6-10117-2013 ◽

2013 ◽

Vol 6 (6) ◽

pp. 10117-10163 ◽

Cited By ~ 2

Author(s):

P. R. Colarco ◽

R. A. Kahn ◽

L. A. Remer ◽

R. C. Levy

Keyword(s):

Optical Thickness ◽

Statistical Significance ◽

Sampling Strategy ◽

Aerosol Optical Thickness ◽

Mean Values ◽

Sampling Artifacts ◽

Aerosol Loading ◽

Decadal Scale ◽

Along Track ◽

The Impact

Abstract. We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Ten different sampling strategies are employed, in which the full MODIS dataset is sub-sampled with various narrow-swath (~400–800 km) and curtain-like (~10 km) along-track configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, the AOT statistics of these sub-samples exhibit significant regional and seasonal biases. These AOT spatial sampling artifacts comprise up to 60% of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swaths exhibit a reduced ability to detect AOT trends with statistical significance, and for curtain-like sampling we do not find any statistically significant decadal-scale trends at all. An across-track sampling strategy obviates the MODIS view angle artifact, and its mean AOT converges to the full-swath mean values for sufficiently coarse spatial and temporal aggregation. Nevertheless, across-track sampling has significant seasonal-regional sampling artifacts, leading to biases comparable to the curtain-like along-track sampling, lacks sufficient coverage to assign statistical significance to aerosol trends, and is not achievable with an actual narrow-swath or curtain-like instrument. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to determine decadal-scale trends or to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.

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