Results 81 to 90 of about 2,253,559 (287)
, 2019 An important feature of Bayesian statistics is the opportunity to do sequential inference: the posterior distribution obtained after seeing a dataset can be used as prior for a second inference.
Thijssen, Bram, Wessels, Lodewyk F. A.
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An Easy to Interpret Diagnostic for Approximate Inference: Symmetric Divergence Over Simulations [PDF]
arXiv, 2021 It is important to estimate the errors of probabilistic inference algorithms. Existing diagnostics for Markov chain Monte Carlo methods assume inference is asymptotically exact, and are not appropriate for approximate methods like variational inference or Laplace's method.
arxiv
, 2009 This paper gives a systematic application of maximum likelihood inference concerning cointegration vectors in non-stationary vector valued autoregressive time series models with Gaussian errors, where the model includes a constant term and seasonal ...
S. Johansen, K. Juselius
semanticscholar +1 more source
Immunoregulatory mechanisms of the arachidonic acid pathway in cancer
FEBS Letters, EarlyView.The central role of the arachidonic acid (AA) pathway in anticancer immunity. Enzymes and metabolites of the AA pathway can play both immunosuppressive and immunostimulatory roles in the tumor microenvironment. Therefore, their tailored targeting could be beneficial as a standalone therapy or in combination with current cancer immunotherapy.
Maria Tredicine +3 more
wiley +1 more source
Wiggles and Curves: The Analysis of Ordinal Patterns
Problemy Zarządzania, 2016 Almost all social science data are analysed with variants of the General Linear Model (GLM): regression analyses, analyses of variance, factor analyses, path analyses and the like.
Warren Thorngate, Chunyun Ma
doaj +1 more source
Generating and Sampling Orbits for Lifted Probabilistic Inference [PDF]
, 2019 A key goal in the design of probabilistic inference algorithms is identifying and exploiting properties of the distribution that make inference tractable.
Broeck, Guy Van den +2 more
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Journal of the Royal Statistical Society Series B: Statistical Methodology, 1953 Summary The subject matter of mathematical statistics may be divided into two parts, the theory of probability and the theory of inference. The first is concerned with deductions from the population to the sample; the second with inferences from the sample to the population, and may further be subdivided into the design and analysis of ...
openaire +1 more source
Molecular Oncology, EarlyView.Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever +1 more
wiley +1 more source
Frontiers in NeuroscienceUnderstanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales. We present a physiologically inspired speech recognition architecture, compatible and scalable with deep learning ...
Alexandre Bittar +2 more
doaj +1 more source
Performance of Some Estimators of Relative Variability
Frontiers in Applied Mathematics and Statistics, 2019 The classic coefficient of variation (CV) is the ratio of the standard deviation to the mean and can be used to compare normally distributed data with respect to their variability, this measure has been widely used in many fields. In the Social Sciences,
Raydonal Ospina +1 more
doaj +1 more source