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Aspects about Statistical Inference [PDF]
Theoretical and Applied Economics, 2006 There are two major types of data sources that can be used when a phenomenon or a variable is investigated: the population and the sample. Based upon the sample, various facts concerning the entire population can be deduced; this process is called ...
Georgeta Vintila +2 more
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Measurement error and statistical disclosure control [PDF]
, 2010 Statistical agencies release microdata to researchers after applying statistical disclosure control (SDC) methods. Noise addition is a perturbative SDC method which is carried out by adding independent random noise to a continuous variable or by ...
Shlomo, Natalie, Natalie Shlomo
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Statistical inferences in phylogeography [PDF]
Molecular Ecology, 2009 AbstractIn conventional phylogeographic studies, historical demographic processes are elucidated from the geographical distribution of individuals represented on an inferred gene tree. However, the interpretation of gene trees in this context can be difficult as the same demographic/geographical process can randomly lead to multiple different ...
Nielsen, R, Beaumont, MA
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, 2009 Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any ...
Shahjahan Khan, Khan, Shahjahan
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An introduction to the maximum entropy approach and its application to inference problems in biology
Heliyon, 2018 A cornerstone of statistical inference, the maximum entropy framework is being increasingly applied to construct descriptive and predictive models of biological systems, especially complex biological networks, from large experimental data sets.
Andrea De Martino, Daniele De Martino
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Simultaneous statistical inference for epigenetic data. [PDF]
PLoS ONE, 2015 Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons ...
Konstantin Schildknecht +2 more
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Towards more accessible conceptions of statistical inference
, 2011 Summary. There is a compelling case, based on research in statistics education, for first courses in statistical inference to be underpinned by a staged development path.
Wild, CJ +5 more
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, 2023 In the 1930s, Psychologists began developing Multiple-Factor Analysis to decompose multivariate data into a small number of interpretable factors without any a priori knowledge about those factors.
Yang, Dan +3 more
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A review of distributed statistical inference
Statistical Theory and Related Fields, 2022 The rapid emergence of massive datasets in various fields poses a serious challenge to traditional statistical methods. Meanwhile, it provides opportunities for researchers to develop novel algorithms.
Yuan Gao +5 more
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Statistical Science, 1993 The three main points of this article are: 1. Quantum mechanical data differ from conventional data: for example, joint distributions usually cannot be defined conventionally; 2. rigorous methods have been developed for analyzing such data; the methods often use quantum-consistent analogs of classical statistical procedures; 3.
Malley, James D., Hornstein, John
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