11 papers · ranked by Valyu relevance
Shuting Liao, Kantharakorn Macharoen, Karen A. McDonald, Somen Nandi + 1 more
We propose a method for analyzing the variability in smooth, possibly nonlinear, functionals associated with a set of product production trajectories measured under different experimental conditions. The key challenge is to make meaningful inference on these parameters across different experimental conditions when only…
Grasiela Casas, Vinicius A.G. Bastazini, Vanderlei J. Debastiani, Valério D. Pillar
Sampling the full diversity of interactions in an ecological community is a highly intensive effort. Recent studies have demonstrated that many network metrics are sensitive to both sampling effort and network size. Here, we develop a statistical framework, based on bootstrap resampling, that aims to assess sampling…
Lijiang Wei, Bin Jing, Haiyun Li
Resting state functional connectivity records enormous functional interaction information between any pair of brain nodes, which enriches the prediction of individual phenotypes. To reduce the high dimensional features in prediction, correlation analysis is a common way for feature selection. However, rs-fMRI signal…
Varun Saravanan, Gordon J. Berman, Samuel J. Sober
A common feature in many neuroscience datasets is the presence of hierarchical data structures, most commonly recording the activity of multiple neurons in multiple animals across multiple trials. Accordingly, the measurements constituting the dataset are not independent, even though the traditional statistical…
Wei Wang, Kevin J. Liu
The 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…
F. Lemoine, J.-B. Domelevo Entfellner, E. Wilkinson, T. De Oliveira + 1 more
Felsenstein’s article describing the application of the bootstrap to evolutionary trees, is one of the most cited papers of all time. That statistical method, based on resampling and replications, is used extensively to assess the robustness of phylogenetic inferences. However, increasing numbers of sequences are now…
Frédéric Lemoine, Olivier Gascuel
Felsenstein’s bootstrap is the most commonly used method to measure branch support in phylogenetics. Current sequencing technologies can result in massive sampling of taxa (e.g. SARS-CoV-2). In this case, the sequences are very close, the trees are short, and the branches correspond to a small number of mutations…
Paul Zaharias, Frédéric Lemoine, Olivier Gascuel
The bootstrap method is based on resampling alignments and re-estimating trees. Felsenstein’s bootstrap proportions (FBP) is the most common approach to assess the reliability and robustness of sequence-based phylogenies. However, when increasing taxon-sampling (i.e., the number of sequences) to hundreds or thousands…
Wancen Mu, Eric Davis, Stuart Lee, Mikhail Dozmorov + 2 more
bootRanges provides fast functions for generation of bootstrapped genomic ranges representing the null sets in enrichment analysis. We show that shuffling or permutation schemes may result in overly narrow test statistics null distributions, while creating new ranges sets with a block bootstrap preserves local genomic…
D. Samuel Schwarzkopf
The problems with classical frequentist statistics are well established, yet the enthusiasm of researchers to adopt alternatives like Bayesian inference remains modest. Here I present the bootstrapped evidence test, an objective resampling procedure that takes the precision with which both the experimental and null…
Vanda M. Lourenço, Joseph O. Ogutu, Rui A.P. Rodrigues, Hans-Peter Piepho
The accurate prediction of genomic breeding values is central to genomic selection in both plant and animal breeding studies. Genomic prediction involves the use of thousands of molecular markers spanning the entire genome and therefore requires methods able to efficiently handle high dimensional data. Not…