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Journal articles on the topic 'Bayesian surprise'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Itti, Laurent, and Pierre Baldi. "Bayesian surprise attracts human attention." Vision Research 49, no. 10 (2009): 1295–306. http://dx.doi.org/10.1016/j.visres.2008.09.007.

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Gijsen, Sam, Miro Grundei, Robert T. Lange, Dirk Ostwald, and Felix Blankenburg. "Neural surprise in somatosensory Bayesian learning." PLOS Computational Biology 17, no. 2 (2021): e1008068. http://dx.doi.org/10.1371/journal.pcbi.1008068.

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Tracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-t

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Bayarri, M. J., and J. Morales. "Bayesian measures of surprise for outlier detection." Journal of Statistical Planning and Inference 111, no. 1-2 (2003): 3–22. http://dx.doi.org/10.1016/s0378-3758(02)00282-3.

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Stern, J. M., and C. A. De Braganca Pereira. "Bayesian epistemic values: focus on surprise, measure probability!" Logic Journal of IGPL 22, no. 2 (2013): 236–54. http://dx.doi.org/10.1093/jigpal/jzt023.

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Correll, Michael, and Jeffrey Heer. "Surprise! Bayesian Weighting for De-Biasing Thematic Maps." IEEE Transactions on Visualization and Computer Graphics 23, no. 1 (2017): 651–60. http://dx.doi.org/10.1109/tvcg.2016.2598618.

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Burns, Kevin. "Computing the creativeness of amusing advertisements: A Bayesian model of Burma-Shave's muse." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 29, no. 1 (2014): 109–28. http://dx.doi.org/10.1017/s0890060414000699.

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AbstractHow do humans judge the creativeness of an artwork or other artifact? This article suggests that such judgments are based on the pleasures of an aesthetic experience, which can be modeled as a mathematical product of psychological arousal and appraisal. The arousal stems from surprise, and is computed as a marginal entropy using information theory. The appraisal assigns meaning, by which the surprise is resolved, and is computed as a posterior probability using Bayesian theory. This model is tested by obtaining human ratings of surprise, meaning, and creativeness for artifacts in a dom

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Visalli, Antonino, Mariagrazia Capizzi, Ettore Ambrosini, Bruno Kopp, and Antonino Vallesi. "Electroencephalographic correlates of temporal Bayesian belief updating and surprise." NeuroImage 231 (May 2021): 117867. http://dx.doi.org/10.1016/j.neuroimage.2021.117867.

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Ostwald, Dirk, Bernhard Spitzer, Matthias Guggenmos, Timo T. Schmidt, Stefan J. Kiebel, and Felix Blankenburg. "Evidence for neural encoding of Bayesian surprise in human somatosensation." NeuroImage 62, no. 1 (2012): 177–88. http://dx.doi.org/10.1016/j.neuroimage.2012.04.050.

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9

Evans, Michael. "Bayesian ikference procedures derived via the concept of relative surprise." Communications in Statistics - Theory and Methods 26, no. 5 (1997): 1125–43. http://dx.doi.org/10.1080/03610929708831972.

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10

Lee, J., Y. Fan, and S. A. Sisson. "Bayesian threshold selection for extremal models using measures of surprise." Computational Statistics & Data Analysis 85 (May 2015): 84–99. http://dx.doi.org/10.1016/j.csda.2014.12.004.

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Avila, Luis, and Ernesto Martínez. "Behavior monitoring under uncertainty using Bayesian surprise and optimal action selection." Expert Systems with Applications 41, no. 14 (2014): 6327–45. http://dx.doi.org/10.1016/j.eswa.2014.04.031.

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Yarnell, Christopher J., Laura M. Jewell, Alex Astell, et al. "Observational study of agreement between attending and trainee physicians on the surprise question: “Would you be surprised if this patient died in the next 12 months?”." PLOS ONE 16, no. 2 (2021): e0247571. http://dx.doi.org/10.1371/journal.pone.0247571.

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Background Optimal end-of-life care requires identifying patients that are near the end of life. The extent to which attending physicians and trainee physicians agree on the prognoses of their patients is unknown. We investigated agreement between attending and trainee physician on the surprise question: “Would you be surprised if this patient died in the next 12 months?”, a question intended to assess mortality risk and unmet palliative care needs. Methods This was a multicentre prospective cohort study of general internal medicine patients at 7 tertiary academic hospitals in Ontario, Canada.

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13

Baldi, Pierre, and Laurent Itti. "Of bits and wows: A Bayesian theory of surprise with applications to attention." Neural Networks 23, no. 5 (2010): 649–66. http://dx.doi.org/10.1016/j.neunet.2009.12.007.

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Ávila, L., and E. Martínez. "Continuous Performance Monitoring of a Closed-Loop Insulin Delivery System Using Bayesian Surprise." Iberoamerican Journal of Industrial Engineering 4, no. 8 (2012): 69–81. http://dx.doi.org/10.13084/2175-8018.v04n08a05.

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Ueda, Kazutaka, Takahiro Sekoguchi, and Hideyoshi Yanagisawa. "How predictability affects habituation to novelty." PLOS ONE 16, no. 6 (2021): e0237278. http://dx.doi.org/10.1371/journal.pone.0237278.

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One becomes accustomed to repeated exposures, even for a novel event. In the present study, we investigated how predictability affects habituation to novelty by applying a mathematical model of arousal that we previously developed, and through the use of psychophysiological experiments to test the model’s prediction. We formalized habituation to novelty as a decrement in Kullback-Leibler divergence from Bayesian prior to posterior (i.e., information gain) representing arousal evoked from a novel event through Bayesian update. The model predicted an interaction effect between initial uncertaint

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Venter, Elmarie. "How and why actions are selected: action selection and the dark room problem." Kairos. Journal of Philosophy & Science 15, no. 1 (2016): 19–45. http://dx.doi.org/10.1515/kjps-2016-0002.

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Abstract In this paper, I examine an evolutionary approach to the action selection problem and illustrate how it helps raise an objection to the predictive processing account. Clark examines the predictive processing account as a theory of brain function that aims to unify perception, action, and cognition, but - despite this aim - fails to consider action selection overtly. He off ers an account of action control with the implication that minimizing prediction error is an imperative of living organisms because, according to the predictive processing account, action is employed to fulfill expe

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Wang, Liang, Xun Liu, Kevin G. Guise, Robert T. Knight, Jamshid Ghajar, and Jin Fan. "Effective Connectivity of the Fronto-parietal Network during Attentional Control." Journal of Cognitive Neuroscience 22, no. 3 (2010): 543–53. http://dx.doi.org/10.1162/jocn.2009.21210.

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The ACC, the dorsolateral prefrontal cortex (DLPFC), and the parietal cortex near/along the intraparietal sulcus (IPS) are members of a network subserving attentional control. Our recent study revealed that these regions participate in both response anticipation and conflict processing. However, little is known about the relative contribution of these regions in attentional control and how the dynamic interactions among these regions are modulated by detection of predicted versus unpredicted targets and conflict processing. Here, we examined effective connectivity using dynamic causal modeling

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Mundhenk, T., W. Einhauser, and L. Itti. "Natural Image RSVP task performance is predicted by measurements of bottom-up Bayesian Surprise exhibited by image sequences." Journal of Vision 8, no. 6 (2010): 682. http://dx.doi.org/10.1167/8.6.682.

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Nour, Matthew M., Tarik Dahoun, Philipp Schwartenbeck, et al. "Dopaminergic basis for signaling belief updates, but not surprise, and the link to paranoia." Proceedings of the National Academy of Sciences 115, no. 43 (2018): E10167—E10176. http://dx.doi.org/10.1073/pnas.1809298115.

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Distinguishing between meaningful and meaningless sensory information is fundamental to forming accurate representations of the world. Dopamine is thought to play a central role in processing the meaningful information content of observations, which motivates an agent to update their beliefs about the environment. However, direct evidence for dopamine’s role in human belief updating is lacking. We addressed this question in healthy volunteers who performed a model-based fMRI task designed to separate the neural processing of meaningful and meaningless sensory information. We modeled participan

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Ballard, Ian, Eric M. Miller, Steven T. Piantadosi, Noah D. Goodman, and Samuel M. McClure. "Beyond Reward Prediction Errors: Human Striatum Updates Rule Values During Learning." Cerebral Cortex 28, no. 11 (2017): 3965–75. http://dx.doi.org/10.1093/cercor/bhx259.

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Abstract Humans naturally group the world into coherent categories defined by membership rules. Rules can be learned implicitly by building stimulus-response associations using reinforcement learning or by using explicit reasoning. We tested if the striatum, in which activation reliably scales with reward prediction error, would track prediction errors in a task that required explicit rule generation. Using functional magnetic resonance imaging during a categorization task, we show that striatal responses to feedback scale with a “surprise” signal derived from a Bayesian rule-learning model an

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FitzGerald, Thomas H. B., Philipp Schwartenbeck, Michael Moutoussis, Raymond J. Dolan, and Karl Friston. "Active Inference, Evidence Accumulation, and the Urn Task." Neural Computation 27, no. 2 (2015): 306–28. http://dx.doi.org/10.1162/neco_a_00699.

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Deciding how much evidence to accumulate before making a decision is a problem we and other animals often face, but one that is not completely understood. This issue is particularly important because a tendency to sample less information (often known as reflection impulsivity) is a feature in several psychopathologies, such as psychosis. A formal understanding of information sampling may therefore clarify the computational anatomy of psychopathology. In this theoretical letter, we consider evidence accumulation in terms of active (Bayesian) inference using a generic model of Markov decision pr

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Cardoso Junior, Moacyr Machado. "Identification and characterization of "Black Swans" in technological events in Brazil." Independent Journal of Management & Production 10, no. 2 (2019): 411. http://dx.doi.org/10.14807/ijmp.v10i2.866.

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“Black swan” events represent a critical issue in risk analysis. Events with extremely low probability of occurrence are in general discarded from the risk analysis process. This paper aims to identify and characterize four accidents that occurred in Brazil into the following classes: “not a black swan”, “black swan: unknown-unknown”, “black swan: unknown-known” and “black Swan: not believed to occur”, by obtaining from experts the distribution of belief for the real probability of each class. Results showed that, throughout all cases analyzed, the class “black swan: unknown-unknown” was never

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23

Dávalos, Eleonora, Leonardo Fabio Morales, Jennifer S. Holmes, and Liliana M. Dávalos. "Opposition Support and the Experience of Violence Explain Colombian Peace Referendum Results." Journal of Politics in Latin America 10, no. 2 (2018): 99–122. http://dx.doi.org/10.1177/1866802x1801000204.

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What factors led to the surprise defeat of the Colombian peace referendum? Initial analyses suggested a link between support for peace and the experience of violence, but economic conditions and political support for incumbent parties also affect electoral outcomes. We use Bayesian hierarchical models to test links between referendum result and previous violence victimization, economic conditions, and support for Centro Democrático (the main party opposed to the peace agreement). There was less support for peace in the Andean region than in other regions, and departments with lower support had

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24

Parmentier, Fabrice B. R., Isabel Fraga, Alicia Leiva, and Pilar Ferré. "Distraction by deviant sounds: disgusting and neutral words capture attention to the same extent." Psychological Research 84, no. 7 (2019): 1801–14. http://dx.doi.org/10.1007/s00426-019-01192-4.

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Abstract Several studies have argued that words evoking negative emotions, such as disgust, grab attention more than neutral words, and leave traces in memory that are more persistent. However, these conclusions are typically based on tasks requiring participants to process the semantic content of these words in a voluntarily manner. We sought to compare the involuntary attention grabbing power of disgusting and neutral words using them as rare and unexpected auditory distractors in a cross-modal oddball task, and then probing the participants’ memory for these stimuli in a surprise recognitio

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25

van de Laar, Thijs, İsmail Şenöz, Ayça Özçelikkale, and Henk Wymeersch. "Chance-Constrained Active Inference." Neural Computation 33, no. 10 (2021): 2710–35. http://dx.doi.org/10.1162/neco_a_01427.

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Abstract Active inference (ActInf) is an emerging theory that explains perception and action in biological agents in terms of minimizing a free energy bound on Bayesian surprise. Goal-directed behavior is elicited by introducing prior beliefs on the underlying generative model. In contrast to prior beliefs, which constrain all realizations of a random variable, we propose an alternative approach through chance constraints, which allow for a (typically small) probability of constraint violation, and demonstrate how such constraints can be used as intrinsic drivers for goal-directed behavior in

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Setiastuti, Sekar Utami. "TIME-VARYING MACROECONOMIC IMPACTS OF GLOBAL ECONOMIC POLICY UNCERTAINTY TO A SMALL OPEN ECONOMY: EVIDENCE FROM INDONESIA." Buletin Ekonomi Moneter dan Perbankan 20, no. 2 (2017): 129–48. http://dx.doi.org/10.21098/bemp.v20i2.809.

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This paper studies macroeconomic impacts of global economic policy uncertainty shocks to a small open economy. To that end, I use monthly Indonesian data along with a measure of global economic policy uncertainty developed by Baker et al. (2016) and Davis (2016) and estimate a time-varying parameter Bayesian structural VAR with non-recursive identification using framework proposed by Canova and Pérez Forero (2015). I find that global economic policy uncertainty shocks lead to a reduction in prices, interest rate, and trade balance in all global events included in the estimation. The impact on

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MABEE, PAULA M., ERICKA A. GREY, GLORIA ARRATIA, et al. "Gill arch and hyoid arch diversity and cypriniform phylogeny: Distributed integration of morphology and web-based tools." Zootaxa 2877, no. 1 (2011): 1. http://dx.doi.org/10.11646/zootaxa.2877.1.1.

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Using the multiple tools available to support an online collaborative environment, we surveyed 62 morphological features from the hyoid arch and gill arches of 53 species of cypriniform fishes that matched those sampled in recent molecularanalyses and two sets of outgroup species (‘Saitoh outgroups’ and ‘Basal outgroups’). This is a skeletal region whose variation is considered historically significant within fishes and Cypriniformes in particular, and we review previous work in light of our own. The clarity of description of characters was enhanced by the use of a community reference ontology

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Wang, Xiaohui, Eric T. Bradlow, Howard Wainer, and Eric S. Muller. "A Bayesian Method for Studying DIF: A Cautionary Tale Filled With Surprises and Delights." Journal of Educational and Behavioral Statistics 33, no. 3 (2008): 363–84. http://dx.doi.org/10.3102/1076998607306080.

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In the course of screening a form of a medical licensing exam for items that function differentially (DIF) between men and women, the authors used the traditional Mantel-Haenszel (MH) statistic for initial screening and a Bayesian method for deeper analysis. For very easy items, the MH statistic unexpectedly often found DIF where there was none. The Bayesian method did not lead the results astray. In this article, the authors describe one possible Bayesian approach for the study of DIF, illustrate its use on this data set, demonstrate situations in which the MH test can be misleading, explore

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Nikitovic, Vladimir. "Demographic future of Serbia from a different angle." Stanovnistvo 51, no. 2 (2013): 53–81. http://dx.doi.org/10.2298/stnv1302053n.

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Based on the assessment of the empirical errors in the official population forecasts of Serbia, the paper shows why forecast users might want a change of the current official concept. The article consists of three parts. The first gives a brief chronological overview of the methods and hypotheses in the official population forecasts of Serbia during the last 60 years. The second refers to the quantification of the past forecast errors in projecting total fertility rate, life expectancy at birth and total population aiming at assessment of the empirical variability. The third part shows the pro

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Jansen, Reinier J., René van Egmond, and Huib de Ridder. "No Alarms and no Surprises: How Qualitative Data Informs Bayesian Inference of Anticipated Alarm Sounds." Procedia Manufacturing 3 (2015): 1750–57. http://dx.doi.org/10.1016/j.promfg.2015.07.480.

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Matthews, Mark, and Tom Kompas. "Coping with Nasty Surprises: Improving Risk Management in the Public Sector Using Simplified Bayesian Methods." Asia & the Pacific Policy Studies 2, no. 3 (2015): 452–66. http://dx.doi.org/10.1002/app5.100.

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Camerer, Colin, and Richard H. Thaler. "In Honor of Matthew Rabin: Winner of the John Bates Clark Medal." Journal of Economic Perspectives 17, no. 3 (2003): 159–76. http://dx.doi.org/10.1257/089533003769204407.

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Matthew Rabin's Clark medal honors his abilities to digest huge amounts of nuanced psychology, create simple models capturing that psychology, and do behavioral economics with those models. After warming up by solving hard problems in modeling pre-game communication, his behavioral career began with a seminal paper on reciprocity. He also created models of “present-bias” in time discounting, and derived some surprises from them, and implications (e.g., deadlinesetting and sin taxes). Matthew has also studied quasi-Bayesian models of judgment biases (confirmation and overgeneralization from sma

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Magnotti, John F., Debshila Basu Mallick, and Michael S. Beauchamp. "Reducing Playback Rate of Audiovisual Speech Leads to a Surprising Decrease in the McGurk Effect." Multisensory Research 31, no. 1-2 (2018): 19–38. http://dx.doi.org/10.1163/22134808-00002586.

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We report the unexpected finding that slowing video playback decreases perception of the McGurk effect. This reduction is counter-intuitive because the illusion depends on visual speech influencing the perception of auditory speech, and slowing speech should increase the amount of visual information available to observers. We recorded perceptual data from 110 subjects viewing audiovisual syllables (either McGurk or congruent control stimuli) played back at one of three rates: the rate used by the talker during recording (the natural rate), a slow rate (50% of natural), or a fast rate (200% of

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Yung, Frances, Kevin Duh, Taku Komura, and Yuji Matsumoto. "A Psycholinguistic Model for the Marking of Discourse Relations." Dialogue & Discourse 8, no. 1 (2017): 106–31. http://dx.doi.org/10.5087/dad.2017.104.

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Discourse relations can either be explicitly marked by discourse connectives (DCs), such as therefore and but, or implicitly conveyed in natural language utterances. How speakers choose between the two options is a question that is not well understood. In this study, we propose a psycholinguistic model that predicts whether or not speakers will produce an explicit marker given the discourse relation they wish to express. Our model is based on two information-theoretic frameworks: (1) the Rational Speech Acts model, which models the pragmatic interaction between language production and interpre

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Liakoni, Vasiliki, Alireza Modirshanechi, Wulfram Gerstner, and Johanni Brea. "Learning in Volatile Environments with the Bayes Factor Surprise." Neural Computation, January 5, 2021, 1–72. http://dx.doi.org/10.1162/neco_a_01352.

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Surprise-based learning allows agents to rapidly adapt to nonstationary stochastic environments characterized by sudden changes. We show that exact Bayesian inference in a hierarchical model gives rise to a surprise-modulated trade-off between forgetting old observations and integrating them with the new ones. The modulation depends on a probability ratio, which we call the Bayes factor surprise, that tests the prior belief against the current belief. We demonstrate that in several existing approximate algorithms, the Bayes Factor Surprise modulates the rate of adaptation to new observations.

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Holmes, Jeremy, and Tobias Nolte. "“Surprise” and the Bayesian Brain: Implications for Psychotherapy Theory and Practice." Frontiers in Psychology 10 (March 28, 2019). http://dx.doi.org/10.3389/fpsyg.2019.00592.

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Pesnot Lerousseau, Jacques, and Daniele Schön. "Musical Expertise Is Associated with Improved Neural Statistical Learning in the Auditory Domain." Cerebral Cortex, May 19, 2021. http://dx.doi.org/10.1093/cercor/bhab128.

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Abstract It is poorly known whether musical training is associated with improvements in general cognitive abilities, such as statistical learning (SL). In standard SL paradigms, musicians have shown better performances than nonmusicians. However, this advantage could be due to differences in auditory discrimination, in memory or truly in the ability to learn sequence statistics. Unfortunately, these different hypotheses make similar predictions in terms of expected results. To dissociate them, we developed a Bayesian model and recorded electroencephalography (EEG). Our results confirm that mus

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Mirza, M. Berk, Rick A. Adams, Karl Friston, and Thomas Parr. "Introducing a Bayesian model of selective attention based on active inference." Scientific Reports 9, no. 1 (2019). http://dx.doi.org/10.1038/s41598-019-50138-8.

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Abstract Information gathering comprises actions whose (sensory) consequences resolve uncertainty (i.e., are salient). In other words, actions that solicit salient information cause the greatest shift in beliefs (i.e., information gain) about the causes of our sensations. However, not all information is relevant to the task at hand: this is especially the case in complex, naturalistic scenes. This paper introduces a formal model of selective attention based on active inference and contextual epistemic foraging. We consider a visual search task with a special emphasis on goal-directed and task-

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Frömer, Romy, Matthew R. Nassar, Rasmus Bruckner, Birgit Stürmer, Werner Sommer, and Nick Yeung. "Response-based outcome predictions and confidence regulate feedback processing and learning." eLife 10 (April 30, 2021). http://dx.doi.org/10.7554/elife.62825.

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Influential theories emphasize the importance of predictions in learning: we learn from feedback to the extent that it is surprising, and thus conveys new information. Here, we explore the hypothesis that surprise depends not only on comparing current events to past experience, but also on online evaluation of performance via internal monitoring. Specifically, we propose that people leverage insights from response-based performance monitoring – outcome predictions and confidence – to control learning from feedback. In line with predictions from a Bayesian inference model, we find that people w

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Parsons, Jacob, Xiaoyue Niu, and Le Bao. "Evaluating the relative contribution of data sources in a Bayesian analysis with the application of estimating the size of hard to reach populations." Statistical Communications in Infectious Diseases 12, s1 (2020). http://dx.doi.org/10.1515/scid-2019-0020.

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AbstractObjectivesWhen using multiple data sources in an analysis, it is important to understand the influence of each data source on the analysis and the consistency of the data sources with each other and the model. We suggest the use of a retrospective value of information framework in order to address such concerns.MethodsValue of information methods can be computationally difficult. We illustrate the use of computational methods that allow these methods to be applied even in relatively complicated settings. In illustrating the proposed methods, we focus on an application in estimating the

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Mason, Alice, Amy Lorimer, and Simon Farrell. "Expected Value of Reward Predicts Episodic Memory for Incidentally Learnt Reward-Item Associations." Collabra: Psychology 5, no. 1 (2019). http://dx.doi.org/10.1525/collabra.217.

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In this paper, we draw connections between reward processing and cognition by behaviourally testing the implications of neurobiological theories of reward processing on memory. Single-cell neurophysiology in non-human primates and imaging work in humans suggests that the dopaminergic reward system responds to different components of reward: expected value; outcome or prediction error; and uncertainty of reward (Schultz et al., 2008). The literature on both incidental and motivated learning has focused on understanding how expected value and outcome—linked to increased activity in the reward sy

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Haarsma, J., P. C. Fletcher, J. D. Griffin, et al. "Precision weighting of cortical unsigned prediction error signals benefits learning, is mediated by dopamine, and is impaired in psychosis." Molecular Psychiatry, June 24, 2020. http://dx.doi.org/10.1038/s41380-020-0803-8.

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Abstract Recent theories of cortical function construe the brain as performing hierarchical Bayesian inference. According to these theories, the precision of prediction errors plays a key role in learning and decision-making, is controlled by dopamine and contributes to the pathogenesis of psychosis. To test these hypotheses, we studied learning with variable outcome-precision in healthy individuals after dopaminergic modulation with a placebo, a dopamine receptor agonist bromocriptine or a dopamine receptor antagonist sulpiride (dopamine study n = 59) and in patients with early psychosis (psy

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Manohar, Anitha Anitha, and Shingo Goto. "Asymmetric Responses of Conditional Variances to Earnings Surprises: A Bayesian Approach." SSRN Electronic Journal, 2005. http://dx.doi.org/10.2139/ssrn.687543.

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Kavanaugh, David, David Maddison, Brian Simison, Sean Schoville, Joachim Schmidt, and Arnaud Faille. "Phylogeny of the supertribe Nebriitae (Coleoptera: Carabidae) based on analyses of molecular sequence data--some surprises." ARPHA Conference Abstracts 2 (June 12, 2019). http://dx.doi.org/10.3897/aca.2.e37156.

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To explore phylogenetic relationships among members of the carabid supertribe Nebriitae, we sampled DNA fragments extracted from adults of 244 nebriite species-group taxa, representing about 25% of known species-group taxa and 93% (38 of 41) of the currently accepted nebriite genus-group taxa. Sequence data were recorded for eight gene fragments (a total of 5654 bases) from nuclear ribosomal, mitochondrial, and nuclear protein coding genes. The resulting phylogeny is based on both individual gene and concatenated gene analyses using Maximum Likelihood and Bayesian methods, which produced nearl

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Of Algebraic Statistics, Journal. "Editorial Messages." Journal of Algebraic Statistics 1, no. 1 (2010). http://dx.doi.org/10.18409/jas.v1i1.3.

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Just as it has been continually happening in the world of mathematical sciences, the group of mathematical scientists led by (for example) Professor Eyup Cetin and his colleagues (who are responsible for the remarkably successful journal, The European Journal of Pure and Applied Mathematics ) have apparently broken the boundaries between pure and applied mathematics by establishing a new journal, the Journal of Algebraic Statistics . I am sure that both the mathematical as well as statistical communities at large will heartily welcome such an interesting and potentially useful addition to the

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