Statistical inference
A Concise Course in Statistical Inference
... The most important aspect of probability theory concerns the behavior of sequences of random variables. This part of probability is called large sample theory or limit theory or asymptotic theory. This material is ...
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Statistical inference from atmospheric time series: detecting trends and coherent structures
... valid statistical inference in a variety of problems, where tradi- tional time series analyses are hindered due to nonlinear data generating mechanisms and limited ...
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Abstract: Interval estimation is one of the most used techniques of statistical inference in
... Abstract: Interval estimation is one of the most used techniques of statistical inference in various areas of science. When the exact analytical solution for interval estimation is not com- putable, an ...
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Bayesian Information Criterion as an Alternative way of Statistical Inference
... The article treats Bayesian information criterion as an alternative to traditional methods of statistical inference, based on NHST.. The comparison of ANOVA and BIC [r] ...
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Tópicos para uma boa análise de dados de estudos empíricos.
... a statistical model, a statistical technique and a statistical receipt; b) Sampling and Design’s implications for statistical validity; c) Complementarities and distinctions between data ...
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Error Orthogonal Models: Structure, Operations and Inference
... in statistical inference and estimation area, calling them quadratic vector ...linear statistical inference, see Seely (1970b, 1971, 1977) and Seely & Zyskind ...
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Forward and backward inference in spatial cognition.
... using statistical inference in a single probabilistic model. Inference is implemented using a common set of ‘lower-level’ computations involving forward and backward inference over ...forward ...
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Cad. Saúde Pública vol.30 número4
... ian methods are not limited to the possibility of incorporating out-of-sample information into the analyses. For example, Bayesian methods are especially useful for statistical inference of complex models ...
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Usefulness of gastric submucosal dissection depth to evaluate skill acquirement in short term training courses in ESD: an experimental study
... This statistical inference indicates that the evaluation of endoscopic resection depth in conjunction with other variables (resection time, en bloc resection rate, size and adverse events) might be ...
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Data-driven inference for the spatial scan statistic
... usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster ...modified inference question: what is the probability that the null ...
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Attribute-value inference using deep neural networks
... No CNN output vector as input jointly with word embedding into CNN + LSTM receives CNN output vector and decode label sequence through LSTM layer + active learning to help reduce relianc[r] ...
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Inference in structural vars with external instruments
... exploit equivariance restriction to left-rotations (respecify SVAR in terms of linear combination of Y’s – this should reduce the dimension of the sufficient statistics in the limit ex[r] ...
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Approximation Capabilities of Interpretable Fuzzy Inference Systems
... become popular [7], [12]. However, there are little studies on effective learning methods of fuzzy inference systems satisfying with interpretability and accuracy. It is desired to develop effective fuzzy systems ...
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Bayesian inference of the evolution of HBV/E.
... This is furthermore supported by a recent study on HBV subgenotype A1 from Africa [36] that uses phylogeographic analyses based on the Bayesian method implemented in BEAST to trace the spread of this subgenotype in and ...
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Semiparametric estimation and inference using doubly robust moment conditions
... We study semiparametric two-step estimators which have the same structure as para- metric doubly robust estimators in their second step. The key difference is that we do not impose any parametric restriction on the ...
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Genetic x Statistical analysis
... Regarding the source of variation Families within the “Set” (F/S), it was found that all of the evaluated characteristics presented significance (p <0.01), proving that there is eno[r] ...
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Statistical assessment on Non-cooperative Target Recognition using the Neyman-Pearson statistical test
... for statistical assessment and ...fitting statistical parameters were applied to the target’s monostatic RCS throughout the X-band frequency range in order to calculate the necessary probabilities to ...
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Robust statistical modeling of portfolios
... This paper is organized as follows. In Section I we propose a statistical model and a robust estimation procedure for a multivariate data. In Section II we apply the proposal to a real data set from emergent ...
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Using Perspective Schema and a Reference Model to Design the ETL Process
... Using inference techniques on queries, they can discover when a set of tuples in a query is contained in, or disjointed from, a set of tuples of another ...
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