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Two-stage sequential estimation procedures for the uniform distribution(Sequential Analysis and Statistical Inference)openaire
Bayes risk and information inequalities(Sequential Analysis and Statistical Inference)
Bayes risk and information inequalities(Sequential Analysis and Statistical Inference)openaire
Stochastic modelling and equilibrium in mathematical finance and statistical sequential analysis
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A General Framework for the Statistical Analysis of Sequential Dyadic Interaction Data
SSRN Electronic Journal, 1988Recent interest in sequential dyadic interactions has motivated researchers to develop methods appropriate for the analysis of such data. After briefly reviewing a series of methodological papers focusing on the analysis of discrete-valued observations, we present a general framework for studying many substantive effects, including dominance and ...
D, Iacobucci, S, Wasserman
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Sequential Pattern Analysis: A Statistical Investigation of Sequence Length and Support
Communications in Statistics - Simulation and Computation, 2013In sequential pattern analysis, the frequency of patterns is evaluated by the support. While computed efficiently from large databases, we show that the support cannot be compared between different databases, since it is influenced by the actual sequence length distribution. Models for this sequence length distribution are surveyed. One of these models,
Christian H. Weiß, Miia Peltola
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About the Effectiveness of the Statistical Sequential Analysis in the Reliability Trials
2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO), 2016The efficiency of the optimal statistical sequential criteria: Wald test, Aivazyan test, Lorden test, Grodzenskiy test in the reliability trials is researched. The reseach is carried out for both continuous distributions (Weibull distribution), and for discrete ones (binomial distribution).
Grodzenskiy Sergey +2 more
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Statistical sequential analysis for detection of microcalcifications in digital mammograms
2010 International Conference on Signal Processing and Communications (SPCOM), 2010We formulate the problem of microcalcification detection in digital mammograms as a statistical change detection problem in the local properties of the image. First, we represent mammograms by two-dimensional autoregressive moving-average (2D ARMA) fields; thus uniquely characterizing the images by their reduced dimensionality 2D ARMA feature vectors ...
Jerzy Zielinski, Nidhal Bouaynaya
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