Results 1 to 10 of about 370,387 (122)
Phylogenetic effective sample size [PDF]
Journal of Theoretical Biology 407:371-386, 2016, 2015 In this paper I address the question - how large is a phylogenetic sample I propose a definition of a phylogenetic effective sample size for Brownian motion and Ornstein-Uhlenbeck processes - the regression effective sample size. I discuss how mutual information can be used to define an effective sample size in the non-normal process case and compare ...
arxiv +8 more sources
International Journal of Ayurveda Research, 2010 Bioactive compounds from marine flora and fauna have extensive past and present use in the treatment of many diseases and serve as compounds of interest both in their natural form and as templates for synthetic modification. Several molecules isolated from various marine organisms (microorganisms, algae, fungi, invertebrates, and vertebrates) are ...
Supriya Bhalerao, Prashant Kadam
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Sample Size Calculations [PDF]
Nephron Clinical Practice, 2011 The sample size is the number of patients or other experimental units that need to be included in a study to answer the research question. Pre-study calculation of the sample size is important; if a sample size is too small, one will not be able to detect an effect, while a sample that is too large may be a waste of time and money. Methods to calculate
Noordzij, M. +3 more
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On the Sampling Size for Inverse Sampling
Stats, 2022 In the Big Data era, sampling remains a central theme. This paper investigates the characteristics of inverse sampling on two different datasets (real and simulated) to determine when big data become too small for inverse sampling to be used and to examine the impact of the sampling rate of the subsamples. We find that the method, using the appropriate
Cuntrera, Daniele +2 more
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Sample compression schemes for balls in graphs [PDF]
SIAM Journal on Discrete Mathematics, 37(4):2585-2616, 2023, 2022 One of the open problems in machine learning is whether any set-family of VC-dimension $d$ admits a sample compression scheme of size $O(d)$. In this paper, we study this problem for balls in graphs. For a ball $B=B_r(x)$ of a graph $G=(V,E)$, a realizable sample for $B$ is a signed subset $X=(X^+,X^-)$ of $V$ such that $B$ contains $X^+$ and is ...
arxiv +1 more source
BaySize: Bayesian Sample Size Planning for Phase I Dose-Finding Trials [PDF]
, 2021 We propose BaySize, a sample size calculator for phase I clinical trials using Bayesian models. BaySize applies the concept of effect size in dose finding, assuming the MTD is defined based on an equivalence interval. Leveraging a decision framework that involves composite hypotheses, BaySize utilizes two prior distributions, the fitting prior (for ...
arxiv +1 more source
Finite Sample t-Tests for High-Dimensional Means [PDF]
arXiv, 2022 Size distortion can occur if an asymptotic testing procedure requiring diverging sample sizes, is implemented to data with very small sample sizes. In this paper, we consider one-sample and two-sample tests for mean vectors when data are high-dimensional but sample sizes are very small.
arxiv
Exact PPS Sampling with Bounded Sample Size [PDF]
arXiv, 2021 Probability proportional to size (PPS) sampling schemes with a target sample size aim to produce a sample comprising a specified number $n$ of items while ensuring that each item in the population appears in the sample with a probability proportional to its specified "weight" (also called its "size").
arxiv
Sample Size Determination [PDF]
ILAR Journal, 2002 Scientists who use animals in research must justify the number of animals to be used, and committees that review proposals to use animals in research must review this justification to ensure the appropriateness of the number of animals to be used.
Rajasekhar Ramakrishnan +2 more
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Sample Size in Natural Language Processing within Healthcare Research [PDF]
arXiv, 2023 Sample size calculation is an essential step in most data-based disciplines. Large enough samples ensure representativeness of the population and determine the precision of estimates. This is true for most quantitative studies, including those that employ machine learning methods, such as natural language processing, where free-text is used to generate
arxiv