Results 41 to 50 of about 14,515,084 (225)

Variational Bayesian Variable Selection for High-Dimensional Hidden Markov Models

Mathematics
The Hidden Markov Model (HMM) is a crucial probabilistic modeling technique for sequence data processing and statistical learning that has been extensively utilized in various engineering applications.
Yao Zhai, Wei Liu, Yunzhi Jin, Yanqing Zhang   +3 more
doaj   +1 more source

The Software Environment R for Official Statistics and Survey Methodology

Austrian Journal of Statistics, 2016
The open-source programming language and software environment R is currently one of the most widely used and popular software tools for statistics and data analysis.
Matthias Templ, Valentin Todorov
doaj   +1 more source

Poissonian bursts in e-mail correspondence

, 2009
Recent work has shown that the distribution of inter-event times for e-mail communication exhibits a heavy tail which is statistically consistent with a cascading Poisson process.
Anteneodo, C., Chialvo, D. R., Malmgren, R. Dean   +2 more
core   +2 more sources

Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study

Research & Politics, 2019
We refute S. Rendón’s recent criticism of the 2003 Peruvian Truth and Reconciliation Commission (TRC) conflict mortality study. We first show that his most important result, an alternative estimate of the mortality due to the Maoist guerrillas of Shining
Daniel Manrique-Vallier, Patrick Ball
doaj   +1 more source

Statistical Methods in Topological Data Analysis for Complex, High-Dimensional Data [PDF]

, 2015
The utilization of statistical methods an their applications within the new field of study known as Topological Data Analysis has has tremendous potential for broadening our exploration and understanding of complex, high-dimensional data spaces.
Doerge, R. W., Medina, Patrick S.
core   +3 more sources

A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation [PDF]

, 2013
Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions.
Blum, M. G. B., Nunes, M. A., Prangle, D., Sisson, S. A.   +3 more
core   +4 more sources

A t-SNE Based Classification Approach to Compositional Microbiome Data

Frontiers in Genetics, 2020
As a data-driven dimensionality reduction and visualization tool, t-distributed stochastic neighborhood embedding (t-SNE) has been successfully applied to a variety of fields.
Xueli Xu, Zhongming Xie, Zhenyu Yang, Dongfang Li, Ximing Xu, Ximing Xu   +5 more
doaj   +1 more source

Introduction to papers on astrostatistics

, 2009
We are pleased to present a Special Section on Statistics and Astronomy in this issue of the The Annals of Applied Statistics. Astronomy is an observational rather than experimental science; as a result, astronomical data sets both small and large ...
Loredo, Thomas J., Rice, John, Stein, Michael L.   +2 more
core   +1 more source

Ranking analysis of F-statistics for microarray data [PDF]

, 2008
Background Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes.
Yuan-De Tan, Myriam Fornage, Hongyan Xu
core   +2 more sources

Statistical analysis of radioimmunoassay data [PDF]

Biochemical Journal, 1972
The statistical processing of radioimmunoassay data is discussed, with special emphasis on fitting the standard curve, screening the data for aberrant readings and combining separate estimations from a single sample.
openaire   +2 more sources