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Philosophy and the practice of Bayesian statistics
, 2010
"... A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually ..."
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Cited by 31 (8 self)
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A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypotheticodeductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework.
A site and timeheterogeneous model of aminoacid replacement
, 2007
"... 1 We combined the CAT mixture model (Lartillot and Philippe 2004) and the nonstationary BP model (Blanquart and Lartillot 2006) into a new model, CATBP, accounting for variations of the evolutionary process both along the sequence and across lineages. As in CAT, the model implements a mixture of d ..."
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Cited by 30 (3 self)
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1 We combined the CAT mixture model (Lartillot and Philippe 2004) and the nonstationary BP model (Blanquart and Lartillot 2006) into a new model, CATBP, accounting for variations of the evolutionary process both along the sequence and across lineages. As in CAT, the model implements a mixture of distinct Markovian processes of substitution distributed among sites, thus accommodating sitespecific selective constraints induced by protein structure and function. Furthermore, as in BP, these processes are nonstationary, and their equilibrium frequencies are allowed to change along lineages in a correlated way, through discrete shifts in global amino acid composition distributed along the phylogenetic tree. We implemented the CATBP model in a Bayesian Markov Chain Monte Carlo framework, and compared its predictions with those of three simpler models, BP, CAT, and the site and timehomogeneous GTR model, on a concatenation of four mitochondrial proteins of 20 arthropod species. In contrast to GTR, BP and CAT, which all display a phylogenetic reconstruction artefact positioning the bees Apis m. and Melipona b. among chelicerates, the CATBP model
Exploratory Data Analysis for Complex Models
, 2002
"... Exploratory" and "confirmatory" data analysis can both be viewed as methods for comparing observed data to what would be obtained under an implicit or explicit statistical model. ..."
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Cited by 29 (7 self)
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Exploratory" and "confirmatory" data analysis can both be viewed as methods for comparing observed data to what would be obtained under an implicit or explicit statistical model.
Markovian Structures in Biological Sequence Alignments
 Journal of the American Statistical Association
, 1999
"... this article, we provide a coherent view of the two recent models used for multiple sequence alignment  the hidden Markov model (HMM) and the blockbased motif model  in order to develop a set of new algorithms that enjoy both the sensitivity of the blockbased model and the flexibility of the ..."
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Cited by 24 (8 self)
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this article, we provide a coherent view of the two recent models used for multiple sequence alignment  the hidden Markov model (HMM) and the blockbased motif model  in order to develop a set of new algorithms that enjoy both the sensitivity of the blockbased model and the flexibility of the HMM. In particular, we decompose the standard HMM into two components: the insertion component, which is captured by the socalled "propagation model," and the deletion component, which is described by a deletion vector. Such a decomposition serves as a basis for rational compromise between biological specificity and model flexibility. Furthermore, we introduce a Bayesian model selection criterion that  in combination with the propagation model, genetic algorithm, and other computational aspects  forms the core of PROBE, a multiple alignment and database search methodology (software available via anonymous ftp at ftp://ncbi.nlm.nih.gov/pub/neuwald/probe1.0). The application of our method to a GTPase family of protein sequences yields an alignment that is confirmed by comparison with known tertiary structures.
Deriving Value from Social Commerce Networks
, 2008
"... Social commerce is an emerging trend in which sellers are connected in online social networks, and where sellers are individuals instead of firms. This paper examines the economic value implications of a social network between sellers in a large online social commerce marketplace. In this marketpl ..."
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Cited by 24 (0 self)
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Social commerce is an emerging trend in which sellers are connected in online social networks, and where sellers are individuals instead of firms. This paper examines the economic value implications of a social network between sellers in a large online social commerce marketplace. In this marketplace each seller creates his or her own shop, and network ties between sellers are directed hyperlinks between their shops. Three questions are addressed: (i) Does allowing sellers to connect to one another create value (i.e., increase sales), (ii) what are the mechanisms through which this value is created, (iii) how is this value distributed across sellers in the network and how does the position of a seller in the network (e.g., its centrality) influence how much it benefits or suffers from the network? We find that: (i) allowing sellers to connect generates considerable economic value; (ii) the network’s value lies primarily in making shops more accessible to customers browsing the marketplace (the network creates a “virtual shopping
Validation of software for bayesian models using posterior quantiles
 Journal of Computational and Graphical Statistics
"... We present a simulationbased method designed to establish that software developed to fit a specific Bayesian model works properly, capitalizing on properties of Bayesian posterior distributions. We illustrate the validation technique with two examples. The validation method is shown to find errors ..."
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Cited by 22 (5 self)
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We present a simulationbased method designed to establish that software developed to fit a specific Bayesian model works properly, capitalizing on properties of Bayesian posterior distributions. We illustrate the validation technique with two examples. The validation method is shown to find errors in software when they exist and, moreover, the validation output can be informative about the nature and location of such errors.
Modern statistics for spatial point processes
, 2006
"... We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs, and ..."
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Cited by 22 (3 self)
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We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs, and Cox process models, diagnostic tools and model checking, Markov chain Monte Carlo algorithms, computational methods for likelihoodbased inference, and quick nonlikelihood approaches to inference.
Bayesian statespace modelling of agestructured data: Fitting a model is just the beginning
 Canadian Journal of Fisheries and Aquatic Sciences
, 2000
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A statespace model for National Football League scores
 Journal of the American Statistical Association
, 1998
"... This paper develops a predictive model for National Football League (NFL) game scores using data from the period 19881993. The parameters of primary interest, measures of team strength, are expected to vary over time. Our model accounts for this source of variability by modeling football outcomes ..."
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Cited by 21 (3 self)
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This paper develops a predictive model for National Football League (NFL) game scores using data from the period 19881993. The parameters of primary interest, measures of team strength, are expected to vary over time. Our model accounts for this source of variability by modeling football outcomes using a statespace model that assumes team strength parameters follow a firstorder autoregressive process. Two sources of variation in team strengths are addressed in our model; weektoweek changes in team strength due to injuries and other random factors, and seasontoseason changes resulting from changes in personnel and other longerterm factors. Our model also incorporates a homefield advantage while allowing for the possibility that the magnitude of the advantage may vary across teams. The aim of the analysis is to obtain plausible inferences concerning team strengths and other model parameters, and to predict future game outcomes. Iterative simulation is used to obtain samples fro...