bluuebunny/crossref_metadata_2025 huggingface dataset:
Incorporating Prior Knowledge in a Marked Point Process Model
Authors: Sølna Knut
Published: November 2023

A procedure for 3D stochastic modelling of geometric deformation of rock caused by tectonic activity will be presented. The rationale is to enable an analysis of the impact of faulting on fluid flow in petroleum reservoirs. The 3D stochastic model for the break patterns occurring in faulted zones is based on the theory of marked point processes. In order to generate realistic break patterns it is necessary to incorporate prior knowledge about the tectonic deformations, and a Bayesian framework making this possible will be specified. Each fault is associated with a prior marginal distribution and probabilistic modelling of spatial interaction between faults enables modelling of homogeneous release of the stress field. Using a Bayesian approach facilitates the incorporation of seismic information as a global constraint. The structural heterogeneities can be reproduced by stochastic simulation, which also makes possible a quantification of the uncertainty associated with the description.
Bayesian Analysis of Generalised Linear Models with Covariate Measurement Error
Authors: Stephens D A , Dellaportas P
Published: November 2023

Use of generalised linear models when covariates are masked by measurement errors is appropriate in many practical epidemiological problems. However, inference based on such models is by no means straightforward. In previous analyses, simplifying assumptions were made. In this paper, we analyse such models in full generality under a Bayesian formulation. In order to compute the necessary posterior distributions, we utilize various numerical and sampling-based approximate and exact techniques. A specific example involving a logistic regression is considered.
On Asymptotic Posterior Normality in the Multiparameter Case
Authors: Sweeting Trevor J
Published: November 2023

Current approaches to demonstrating asymptotic posterior normality in the multiparameter case fail to cover certain cases where the data arise from a stochastic process. In this paper we present a set of hypotheses for asymptotic posterior normality which are satisfied in such cases. Continuity-type conditions on observed information are imposed on suitable shrinking neighbourhoods and workable conditions relating to the tail behaviour of the posterior distribution are given. The theory is illustrated with an example of a two-parameter nonhomogeneous Poisson process.
REML estimation of variance components and analysis of unbalanced designs
Authors: Payne R W , Lane P W , Digby P G N , Harding S A , Leech P K , Morgan G W , Todd AD , Thompson R , Wilson G Tunnicliffe , Welham S J , White R P
Published: November 2023

This chapter describes the facilities for estimation of variance components and analysis of linear mixed models using the method of residual maximum likelihood (REML), sometimes also known as restricted maximum likelihood.

The REML algorithm estimates the treatment effects and variance components in a linear mixed model: that is, a linear model with both fixed and random effects. Like regression, REML can be used to analyse unbalanced data sets; but, unlike regression, it can also account for more than one source of variation in the data, providing an estimate of the variance components associated with the random terms in the model.
The first Americans: different waves of migration to the New World inferred from mitochondrial DNA sequence polymorphisms
Authors: Horai Satoshi , Kondo Rumi , Sonoda Shunro , Tajima Kazuo
Published: November 2023

Mongoloid descendants are now distributed over a wide area of the Pacific-rim region, having adapted to a variety of environments. One of the major issues for research into the prehistoric dispersal of Asiatic Mongoloid peoples is the question of the first Americans, the ‘peopling of the New World’. No authority doubts that the ancestors of Native Americans came from northeast Asia across the Bering land bridge, then dispersed and settled in various parts of the Americas, and finally reached the southernmost part of South America. How ever, when they came and with what genetic backgrounds and cultures is not yet fully resolved.
Early agriculture and the dispersal of the southern Mongoloids
Authors: Bellwood Peter
Published: November 2023

In my archaeological and linguistic perspective on southeast Asia (e.g. Bellwood 1985, 1991a, 1992a) I have taken the view that populations ancestral to present day Mongoloids began to colonize the region from the north during the early phases of dependence on agriculture. This colonization started in the fourth millennium BC and is continuing locally in some remote regions today. In eastern Indonesia these incoming Mongoloid groups intermarried gradually with the Melanesian populations who already occupied the area in relatively high den sities. While pre-agricultural populations with some clinal degrees of Mongoloid affinity might have existed in the northern and western parts of southeast Asia, the southeast Asian Mongoloid populations as a whole cannot have evolved in situ within southeast Asia from low latitude Pleistocene forerunners, separate from the major (and obviously related) populations of east Asian Mongoloids outside the tropics. The phenotypic trends in skin pigmentation and hair form developed due to equatorial propinquity elsewhere in the Old World (Africa, southern India, Australia, Melanesia) do not occur in this region (Bellwood 1985; Robbins 1991). The southeast Asian Mongoloids do not represent an equatorial adaptation, except on a superficial level. They must have expanded, allowing for intermarriage with indigenous populations, into their southern regions of distribution from somewhere north of the tropics.
Are animal experiments in toxicological research the ‘right’ size?
Authors: Morgan B J T
Published: November 2023

The use of animals in biomedical research involves complex ethical issues. Whether or not any pain and suffering experienced by the animals can be justified in terms of better future human and animal health is hotly debated. However, both scientists and those concerned with animal welfare would agree that the unnecessary or wasteful use of animals cannot be justified.
Estimating dose-response for toxic end-points
Authors: Salsburg David
Published: November 2023

The above quotation lies at the heart of almost all toxicological investigations. It tends to be ignored in the popular press and in political discussions of the consequences of these investigations, so we often read about ‘toxic substances’ that are ‘the most toxic known to man’ or that are ‘very toxic’. The resulting political debates sometimes assume that some substances are ‘toxic’ and some are not. Then, the debate is over whether a particular substance belongs in that class. However, a little careful thought about the biological effects of chemicals will soon produce a Paracelsian conclusion. One molecule of anything is not going to produce damage to a living organism; and enough of anything, no matter how essential it may be to life, will kill. The ability of modern analytical chemistry to detect levels of contaminants down to the parts per billion level has made it essential that even the political debates come back to Paracelsus’ insights.
Overdispersion in logistic-linear models
Authors: Williams David A
Published: November 2023

The logistic-linear model is well established as the basis for analysing regression data, or data from a designed experiment, when the response variable is a proportion. Suppose that the data consist of a set of n cases. In the ith case ri successes, mi - ri failures, and a vector Xi of p explanatory variables are recorded. The logistic-linear model assumes that the ri are realizations of random variables Ri distributed independently Binomial(mi, θi), where θi is related to a linear predictor through the logistic link logit(θi) = log{θi/(l - θi)} = ηi;• An alternative link is the probit, given by probit(θi) = -1(θi) = ηi, where <1>-1 denotes the inverse Normal distribution function.
Exploratory and model-based inference in toxicokinetics
Authors: Urfer W
Published: November 2023

Risk assessment of potentially harmful chemicals is fundamental in toxicology. Thorough research depends on When animals serve as models of human systems, a critical step is extrapolation from the risk observed in the experimental animals to the risk associated with the human organism. To avoid serious error, the researcher must consider both toxicokinetics in specific experimental animals (including uptake, distribution, elimination, and metabolism of the chemicals), as well as interspecific differences among various animals.
Bayesian Questions and Answers in Queues¹
Authors: Armero C , Bayarri M J
Published: November 2023

A queueing system occurs when “customers” arrive at some facility requiring a certain type of “service” provided by the “servers”. Both the arrival pattern and the service requirements are usually taken to be random. If all servers are busy when customers arrive, they usually wait in line to get served. The statistical analysis of queueing systems poses a number of interesting and challenging questions and Bayesian methods are especially well suited to deal with them. In this paper we address some of these questions for a number of Markovian queueing systems, in which both the interarrival and the service time are assumed to be exponential, and the number of servers can vary.
Plausible Bayesian Games
Authors: Smith J Q
Published: November 2023

Many situations which a Bayesian wants to model, especially when in an economic or business environment, are, in essence, complicated games between more than one player. In this paper I discuss the extent to which I believe ideas of rationality can help a Bayesian to formulate practical and plausible models of her competitors’ behaviour. A Bayesian model is a subjective representation of the world as that Bayesian sees it. One purpose is to provoke others into adjusting their own beliefs structures after studying it. To have an impact, therefore, every Bayesian model should be supported by well-reasoned arguments about the various modelling assumptions on which it is based. The aim of this paper is to discuss how these arguments might be constructed and then appraised when the model of interest concerns the behaviour of more than one rational decision maker.
Intrinsic Priors via Kullback-Leibler Geometry
Authors: Dmochowski J
Published: November 2023

In Bayesian model selection or hypothesis testing problems the Bayes factor (BF) cannot be used directly if at least one of the priors is improper. Berger and Pericchi (1993) proposed the use of the so-called intrinsic Bayes factor (IBF). The IBF is a Bayes factor (BF) multiplied by a data dependent “correction” term. The asymptotic behavior of both the BF and the “correction” term will be described in the iid case. Intrinsic priors are priors for which the resulting BF is asymptotically equivalent to the IBF. Asymptotic considerations lead to one (nested case) or two (non-nested case) functional equations. These intrinsic equations involve Kullback-Leibler projections. A geometrical interpretation and the general form of the solutions for the nested case will be presented and illustrated through examples.
Conditional External Bayesianity in Decomposable Influence Diagrams
Authors: Faria A E , Smith J Q
Published: November 2023

This paper addresses the group decision problem, where the members of a group may be jointly responsible for a decision. We shall assume that the group has agreed on the structure of associations of variables in a problem, as might be represented by a commonly agreed influence diagram (ID). However, the members of that group diverge about the actual conditional probability distributions for the variables in that ID. The algorithm we suggest they adopt is one which demands, at least on learning information which preserves the ID structure, that the pool of conditional distributions associated with the ID are externally Bayesian (EB). It is illustrated why such a generalisation of external Bayesianity is practically quite useful.
Bayes Factors, Nuisance Parameters and Imprecise Tests
Authors: Verdinelli I , Wasserman L
Published: November 2023

Bayes factors are often used to test precise null hypotheses. One objection to the Bayes factor B is that a precise null hypothesis can sometimes be unrealistic. But it can be shown that B approximates the Bayes factor for an imprecise null hypothesis, under very mild conditions. We show that a similar approximation holds when there are nuisance parameters. Specifically, if the likelihood is bounded and continuous, then it suffices that the prior under the null hypothesis be the geometric conditional of the prior under the alternative. The form of the conditional is determined by the sequence of approximating null hypotheses. If the likelihood is not continuous, it may not be possible to approximate an imprecise test with the precise test.
Bayes Linear Adjustment for Variance Matrices
Authors: Wilkinson D J , Goldstein M
Published: November 2023

We examine the problem of covariance belief revision using a geometric approach. We exhibit an inner-product space where covariance matrices live naturally—a space of random real symmetric matrices. Toe inner product on this space captures aspects of our beliefs about the relationship between covariance matrices of interest to us, providing a structure rich enough for us to adjust beliefs about unknown matrices in the light of data such as sample covariance matrices, exploiting second-order exchangeability specifications.
On Improving a Model for Combining Experts’ Forecasts
Authors: Wiper M P , Pettit L I
Published: November 2023

In Wiper and French (1994), a model was introduced for updating a Decision Maker’s forecasts in the light of hearing an expert’s quantiles for the forecast variable. This model contained the unrealistic assumption that the Decision Maker believed it possible that the expert’s quantiles could be unordered. Here, we use the Gibbs sampler to remove this flaw in the initial model.
Local spectral theory for multipliers
Authors: Laursen Kjeld B , Neumann Michael M
Published: November 2023

This chapter is devoted to the discussion of an area where spectral theory, harmonic analysis, and the theory of Banach algebras overlap and interact. Our main interest is in the spectral properties of convolution operators on certain group or measure algebras. A general frame is provided by the theory of multipliers on commutative Banach algebras. The simple and natural notion of a multiplier extends that of a multiplication operator, and leads to a uniform approach to convolution operators in various settings. The basics of this theory and a series of important examples are presented in Section 4.1.
Practitioners and Patricians
Authors: Field J V
Published: November 2023

Choosing to look exclusively at first class works of art has its disadvantages for the historian. Among other things, one tends to avoid seeing the snags inherent in a particular style. For the fifteenth and sixteenth centuries, excellent correctives are available, both in the form of second class works of art and in the form of unkind comments by artists about other people’s work. Renaissance man, as revealed in the vivid pages of Niccolo Machiavelli’s The Prince (written in 1513), is chiefly characterised by his determination to see off the opposition.
Large deviations of stationary reflected Brownian motions
Authors: Majewski Kurt
Published: November 2023

Large deviation principles (LDPs) for queue length distributions of queueing systems are of great interest for the analysis of tail probabilities and thus for the analysis of the performance of these systems. So far, for queueing systems with more than one queue LDPs are only available in particular cases; see Bertsimas et al. (1994), Dupuis and Ellis (1995) and O’Connell (1996). Working in a heavy traffic regime, stochastic queueing networks can be approximated by multidimensional reflected Brownian motions (RBMs); see Harrison and Nguyen (1993). In particular, for multiclass feedforward queueing systems Peterson (1991) proved the weak convergence of the properly scaled workload process to an RBM, when the traffic intensity converges to one with a certain speed. Here, a feedforward queueing system is a queueing system in which the nodes can be numbered in such a way that each customer is routed along nodes with increasing numbers. The resulting limit RBMs, which we call foedforward RBMs, have a reflection matrix of the form (I+ Q)-1, where I is the identity matrix and Q is a lower diagonal matrix with non-negative entries. In this paper, we prove an LDP for the steady-state distribution of feedforward RBMs. We also give an example of an explicit calculation of a certain large deviation rate.
Admission controls for loss networks with diverse routing
Authors: MacPhee lain , Ziedins Ilze
Published: November 2023

This paper studies control policies for large symmetric star-shaped loss networks, in which arrivals request capacity on one or two links. We formulate the optimization problem of interest for the network, and consider the limit as the number of links in the network becomes large while the arrival rate and capacities at any single link are held fixed. The optimal solution of the time-independent version of the deterministic problem obtained in this limit is to use a threshold policy, also known as trunk reservation. This work complements that of Hunt and Laws for fully connected networks.
Flexible Discriminant and Mixture Models
Authors: Hastie Trevor , Tibshirani Robert , Buja Andreas
Published: November 2023

Fisher’s linear discriminant analysis is a useful and graphical tool for multi-group classification. With a large number of predictors, one can find a reduced number of discriminant coordinate functions that are ‘optimal’ for separating the groups. With two such functions one can produce a classification map that partitions the reduced space into regions that are identified with group membership, and the decision boundaries are linear.
Developmental Origins of Astrocytes
Authors: Goldman J E
Published: November 2023

Astrocytes, the delicate, multiprocessed glial cells of the central nervous system (CNS), were first visualized over a century ago (Andriezen, 1893), and at that time were noted for their complex shapes, in which thicker processes branch into ever-thinner ones. Although many astrocytes are indeed ‘star-shaped’, they in fact display a wide variety of morphologies, among them the spherical or ovoid protoplasmic glia of gray matter; the more irregular and less complex fibrous astrocytes of white matter; the Bergmann glia of the cerebellar molecular layer, whose processes are oriented radially from the Purkinje cell layer to the pial surface; the velate astrocytes of the cerebellar granule cell layer, whose sheet-like processes wrap mossy fiber terminals; and the radially oriented glia that populate the periventricular regions of the diencephalon and brainstem. All share certain salient characteristics, such as numerous branching processes, intermediate filaments in the cell cytoplasm and intimate contact with mesenchymal elements of the blood vessels and pial surfaces and with neurons.
Analysis of Longitudinal Data
Authors: Diggle Peter J , Heagerty Patrick J , Liang Kung-yee. , Zeger Scott L
Published: November 2023

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models for discrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This new edition of Analysis for Longitudinal Data provides a thorough and expanded revision of this important text. It includes two new chapters; the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.
Plant structure: the solidity of anti-herbivore protection
Authors: Schoonhoven Louis M , Loon Joop J A van , Dicke Marcel
Published: November 2023

A clear understanding of insect-plant relationships requires fairly detailed knowledge of plant structures and chemicals involved in resistance to most insects and susceptibility to others. The present Chapter deals with the morphological (physical) factors that interfere with feeding or oviposition, and Chapter 4 considers plant chemicals that affect insect behaviour and physiology.
Plant chemistry: endless variety
Authors: Schoonhoven Louis M , Loon Joop J A van , Dicke Marcel
Published: November 2023

The subject of this Chapter-plants as food for herbivorous insects-touches the heart of insect plant biology. Its theme can be captured in two basic questions. First, what do plants offer to insects by way of nutrition? And second, what do insects need for optimal growth and reproduction? Answering these two questions isseriously hindered by the fact that (1) the chemical composition of plants, as noted before, varies among species in both space and time, and (2) the nutritional requirements of insects vary between species and with developmental stage and environmental conditions.
Insects and flowers: mutualism par excellence
Authors: Schoonhoven Louis M , Loon Joop J A van , Dicke Marcel
Published: November 2023

When C. K. Sprengel, rector of a Lutheran school in Germany, became depressed as a result of his duties, his doctor advised him to study Nature and, to facilitate his recovery, taught his patient some elementary botany. Sprengel then gained an in-depth knowledge of flower morphology, nectar secretion and its function, and published in 1793 a treatise under the imaginative title Das entdeckte Geheimniss der Natur im Bau und in der Befruchtung der Blumen (The Secret of Nature revealed in the Structure and Fertilization of Flowers; Fig. 12.1).
Magnetoencephalography
Authors: Rosburg Timm , Sauer Heinrich
Published: November 2023

Magnetoencephalography (MEG) devices permit the observation of magnetic fields stemming from electrical brain activity. MEG is, therefore, like electroencephalography (EEG), a method to record brain activity with a time resolution of milliseconds. The high temporal resolution is an important feature for the study of human brain function, as recent findings have stressed the importance of high-frequency signals in cortical information processing. Gamma-band activity (in the range of 40 Hz) is thought to play a key role in human information processing (Varela et al. 2001) and some sensory information seems to be processed even at much higher frequencies (~600 Hz) (Curio et al. 1994). Although EEG and MEG share some similarities, there are some considerable differences, which lead to slightly different applications. The differences between the methods are discussed here briefly—the reader who is interested in methodological and practical issues of MEG in more detail is referred to Hämäläinen et al. (1993) or Elbert (1998).
Towards an integrated imaging of schizophrenia
Authors: Lawrie Stephen M , Johnston Eve C , Weinberger Daniel R
Published: November 2023

The preceding chapters in this book demonstrate both the great advances in technology applied to brain imaging and knowledge of schizophrenia gained from these techniques over the past 25 years or so. In this chapter, we aim to synthesize the findings from these studies, in the light of other improvements in our understanding of schizophrenia and related neuropsychiatric conditions—particularly those deriving from genetics, epidemiology, and cognitive neuropsychology. We consider the conceptual and methodological problems of the field, and indicate where we think definite progress is likely in the foreseeable future (e.g. scanning both special and representative populations, multi-modal imaging, employing complementary approaches to study disconnectivity, and using neuroimaging databases).
Hierarchical Bayesian Models for Applications in Information Retrieval
Authors: Jordan David M , Blei. Michael I , Ng Andrew Y
Published: November 2023

The field of information retrieval is broadly concerned with the problem of organizing collections of documents and other media so as to support various information requests on the part of users. The familiar problem of returning a subset of documents in response to a query lies within the scope of information retrieval, as do the problems of analyzing cross-referencing within a document collection, analyzing linguistic structure so as to be able to say who did what to whom, automatic compilation of document summaries, and automatic translation. Another class of problems involve analyzing interactions between users and a collection, including the “collaborative filtering” problem in which suggestions are made to new users of a system based on choices made by previous users.
Bayesian Nonparametric Inference for Mixed Poisson Processes
Authors: Gutiérrez-Pena Eduardo , Nleto-Barajas Luise E
Published: November 2023

In the theory of stochastic processes there are two that are fundamental. One is the Weiner model of Brownian motion; the other is the Poisson process. Both are important instances of exponential families of stochastic processes (Kiichler and Sorensen, 1997). The Poisson process has several interesting properties and characterizations. For one thing, it is the only point process with stationary and independent increments. In addition, Poisson processes are ordinary renewal processes with exponentially distributed inter-occurrence times; they are the only ordinary renewal processes that are also stationary. For a thorough account of the structure and properties of general Poisson processes, the reader is referred to Kingman (1993).
Bayesian Clustering with Variable and Transformation Selections
Authors: Liu Jun S , Zhang JunniL , Palumbo Michael J , Lawrence Charles E
Published: November 2023

The clustering problem has attracted much attention from both statisticians and computer scientists in the past 50 years. Methods such as hierarchical clustering and the K-means method are convenient and competitive first choices off the shelf for the scientist. Gaussian mixture modelling is another popular but computationally expensive clustering strategy, especially when the data are high-dimensional. We propose to first conduct a principal component analysis (PCA) or correspondence analysis (CA) for dimension reduction, and then fit Gaussian mixtures to the data projected to the several major PCA or CA directions. Two technical difficulties of this approach are: (a) the selection of a subset of the PCA factors that are informative for clustering, and (b) the selection of a proper transformation for each factor. We propose a Bayesian formulation and Markov chain Monte Carlo strategies that overcome the two difficulties and examine the performances of the new method by both simulation studies and real applications in molecular imaging analysis and DNA microarray analysis.
A Statistical Approach to Modeling Genomic Aberrations in Cancer Cells
Authors: Michael A , Yang Newton Hyuna , Tomlinson Patricia A Gorman Ian , Roylance Rebecca R
Published: November 2023

Whereas most cells in the body carry the normal complement of 23 chromosome pairs, the cells within a cancerous tumor very often present highly abnormal genomic structure. Deletions, amplifications, rearrangements and mutations are common at various scales and are highly variable amongst tumors, as indicated by molecular technologies which enable ever better measurement. It is an important statistical problem to separate sporadic abnormalities from those that may not be sporadic and that may have some biological significance. We discuss a modelling strategy for genomic aberration data, which allows us to to infer combinations of aberrations that together increase the chance that a precancerous cell will have a descendant tumor lineage. The likelihood component involves a network of pathway structures. Markov chain Monte Carlo is used to sample from the space of these oncogenic networks. We illustrate the methodology with comparative genomic hybridizations from a recent breast cancer study, and we derive a likelihood formula for the larger class of tree-like networks.
Identifying Mixtures of Regression Equations by the SAR procedure
Authors: Rodríguez Daniel Peña Julio , Tiao George C
Published: November 2023

A procedure for identifying data heterogeneity when fitting regression models is presented. The method is based on the SAR procedure, developed by Pena and Tiao (2002), and has three steps. First, the sample is cleaned for large outliers by using a discrepancy measure based on predictive ordinates. Second, observations are split into small homogeneous groups by using a link function derived from cross-validation predictive distributions. Third, these small groups are then iteratively enlarged by incorporating observations homogeneous to those in the group. In this way the possible piece-wise regression equations are found. Examples are shown to illustrate the performance of the procedure for finding mixtures of regressions due to the presence of outliers or to switching regression models. A Monte Carlo study of the power of the proposed procedure is presented.
Measures of Incoherence: How not to Gamble if you Must
Authors: Seidenfeld Mark L Schervish. Teddy , Kadane Joseph B
Published: November 2023

The degree of incoherence, when previsions are not made in accordance with a probability measure, is measured by the rate at which an incoherent bookie can be made a sure loser. We consider each bet from three points of view: that of the gambler, that of the bookie, and a neutral viewpoint. From each viewpoint, we define a normalization for each bet, and the sure loss for incoherent previsions is divided by the normalization to determine the rate of incoherence. Several different definitions of normalization are considered in order to determine plausible ranges for the degree of incoherence. We give examples of the measurement of incoherence of of some classical statistical procedures.
A Novel Framework for Tracking Groups of Objects
Authors: Zohar Ron , Geiger Dan
Published: November 2023

We describe a novel framework for group tracking and identification termed flow conservation group tracking. Our framework integrates local kinematic measurements with flow conservation constraints so as to yield a robust estimation of the positions and types of targets across an arena. The framework is based on three components each of which is novel. The measurement-to-track component uses a reduction to minimum cost flow problems. The estimation of the number of objects on each track is based on estimation using flow networks, and the assessment of the types of vehicles is reduced to hierarchy matching algorithms.
Expected Utility Estimation via Cross-Validation
Authors: Vehtari Aki , Lampinen Jouko
Published: November 2023

We discuss practical methods for the assessment, comparison and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model is to estimate its future predictive capability by estimating expected utilities. Instead of just making a point estimate, it is important to obtain the distribution of the expected utility estimate in order to describe the associated uncertainty. We synthesize and extend the previous work in several ways. We give a unified presentation from the Bayesian viewpoint emphasizing the assumptions made and propose practical methods to obtain the distributions of the expected utility estimates. We discuss the properties of two practical methods, the importance sampling leave-one-out and the A’-fold cross-validation. We propose a quick and generic approach based on the Bayesian bootstrap for obtaining samples from the distributions of the expected utility estimates. These distributions can also be used for model comparison, for example, by computing the probability of one model having a better expected utility than some other model. We discuss how the cross-validation approach differs from other predictive density approaches, and the relationship of cross-validation to information criteria approaches, which can also be used to estimate the expected utilities. We illustrate the discussion with one toy and two real world examples.
Psychoanalysis: An Introduction to the Philosophy of Science (Co-author: Paul Sturdee)
Authors: Fulford K W M , Thornton Tim , Graham George
Published: November 2023

Science or non-sense? Along with other areas of human activity, medicine has reaped enormous rewards from science. Casting off myth and received authority, its history has been a history of progress—Vesalius, Harvey, Morgagni, Sydenham, Pasteur, Jenner, Currie, Fleming … the great names ring down the centuries. Signs and symptoms are defined; diseases discovered; new treat- ments established; causal theories refined; and in this century in particular, all this has culminated in unprecedented improve- ments for many in life expectancy and freedom from disease.
The empirical basis for cosmological theorie
Authors: Rowan-Robinson Michael
Published: November 2023

We can make progress towards answering the questions ‘what is the structure of the universe?’ and ‘how has the universe changed with time?’ only if we believe that the universe has a simple over-all structure. In our immediate locality the universe has an exceedingly complex structure. If we had to construct a mathematical model of the human brain, and had as little observational information about it as we have about the universe, we would hardly know where to start. However, a human brain is a highly atypical region of the universe. For one thing its density is about 1030 times the present average density of matter in the universe.
Early stages of the big bang
Authors: Rowan-Robinson Michael
Published: November 2023

So far we have constructed models of universes filled only with matter. Although radiation contributes less than 1 per cent of the average energy per unit volume in the universe at the present epoch, it plays a crucial and dominant role in the early stages. We can study the evolution of a universe containing matter and radiation by applying the first law of thermodynamics to an element of the substratum. This gives the same answer as applying the full field equations of general relativity.
Separate Modifiability and the Search for Processing Modules
Authors: Sternberg Saul
Published: November 2023

One approach to understanding a complex process or system starts with an attempt to divide it into modules: parts that are independent in some sense, and functionally distinct. In this chapter I discuss a method for the modular decomposition of neural and mental processes that reflects recent thinking in psychology and cognitive neuroscience. This process- decomposition method, in which the criterion for modularity is separate modifiability, is contrasted with task comparison and its associated subtraction method. Four illustrative applications of process decomposition and one of task comparison are based on the event-related potential (ERP), transcranial magnetic stimulation (TMS), and functional magnetic resonance imaging (fMRI).
Models of Incompressible Fluid Flow
Authors: Elman Howard C , Silvester David J , Wathen Andrew J
Published: November 2023

To set the scene for subsequent chapters, the basic PDE models that are the focus of the book are derived in this chapter. Our presentation is rudimentary. Readers who would like to learn more about the physics underlying fluid flow modelling are advised to consult the books of Acheson [1] or Batchelor [12]. The fundamental principles are conservation of mass and conservation of momentum, or rather, that forces effect a change in momentum as described by Newton’s famous Second Law of Motion.
The Navier-Stokes Equations
Authors: Elman Howard C , Silvester David J , Wathen Andrew J
Published: November 2023

The Navier-Stokes system is the basis for computational modeling of the flow of an incompressible Newtonian fluid, such as air or water.
Probability distributions
Authors: Lindsey J K
Published: November 2023

In Chapter 2, we looked at a family of models, the logistic and log linear models. to describe how the shape of a probability distribution changes in different subgroups of a population. However, because the response in these models is nominal, their multinomial distributions (and their histogram representations) can take any form. (See, for example, Figure 1.2.) These types of models are really the only ones possible for independent observations when the response is nominal (although there are various possibilities for linking the probabilities to the explanatory variables instead of the log or logit).
Identifying neurocognitive phenotypes in autism
Authors: Tager-Flusberg Helen , Joseph ,Robert M
Published: November 2023

Autism is a complex disorder that is heterogeneous both in its phenotypic expression and its ethology. The search for genes associated with autism and the neurobiological mechanisms that underlie its behavioural symptoms has been hampered by this heterogeneity. Recent studies indicate that within autism, there may be distinct subgroups that can be defined based on differences in neurocognitive profiles. This paper presents evidence for two kinds of subtypes in autism that are defined on the basis of language profiles and on the basis of cognitive profiles. The implications for genetic and neurobiological studies of these subgroups are discussed, with special reference to evidence relating these cognitive phenotypes to volumetric studies of brain size and organization in autism.
Babylonian mathematics
Authors: Hodgkin Luke
Published: November 2023

Obviously the pioneers and masters of hydraulic society were singularly well equipped to lay the foundations for two major and interrelated sciences: astronomy and mathematics. (Wittfogel, Oriental Despotism, p. 29, cited Høyrup 1994, p. 47) Based on intensive cereal agriculture and large-scale breeding of small livestock, all in the hands of a centralized power, [this civilization] was quickly caught up in a widespread economy which made necessary the meticulous control of infinite movements, infinitely complicated, of the goods produced and circulated. It was to accomplish this task that writing developed; indeed for several centuries, this was virtually its only use.
Lipschitz functions in metric spaces
Authors: Ambrosio Luigi , Tilli Paolo
Published: November 2023

This chapter is entirely devoted to Lipschitz functions and their connections with Hausdorff measures. A comprehensive treatment of this topic is provided in Federer 19, Chapters 2 and 3]; see also Evans and Gariepy 17] and Ambrosio et al. 6].
Sobolev spaces in a metric Framework
Authors: Ambrosio Luigi , Tilli Paolo
Published: November 2023

In this section we define a class of Sobolev functions between metric spaces, essentially following the original definition of Haj-las1 27] for real-valued functions. We refer to Haj-las1 and Koskela 28] for a complete overview on this quickly developing area see also Cheeger 9], Franchi et al. 20], Shanmugalingam 53], Heinonen 29], and Heinonen et al. 30] .
Gene Genealogies, Variation and Evolution
Authors: Hein Jotun , Schierup Mikkel H , Wiuf Carsten
Published: November 2023

Coalescent theory is a central concept in the study of genetic sequence variation that probabilistically describes the genealogy relating the sampled sequences. In this text, besides fulfilling the glaring need for such a book, the authors present this theory in a straightforward and elementary manner and describe the statistical and computational methods used in modelling and analyzing genetic sequence variation. Rich in examples and illustrations the book covers basic concepts, complications arising from geographical structure and recombination before considering aspects of statistical inference based on these models. The book ends with chapters on Gene Mapping, which combines sequence variation data with phenotypic data (such as disease) to define areas of the genome where genes are responsible for the trait, and Human Evolution, a research area that is experiencing a renaissance due to the enormous amounts of data produced in molecular studies. Authored by leading experts, this seminal text presents a straightforward and elementary account of coalescent theory, which is a central concept in the study of genetic sequence variation observed in a population. It is highly suitable for a graduate course in statistics, population, molecular and medical genetics, bioscience and medicine and students studying the evolution of human population and disease, and will be an invaluable reference for bioscientists and statisticians in the pharmaceutical industry and academia
Long-term potentiation in the Eocene
Authors: Lynch G
Published: November 2023

The first ten years of long-term potentiation (LTP) research are reviewed. Surprisingly, given the intensity of current interest, the discovery paper did not trigger a wave of follow-on experiments. Despite this, the initial work laid out what ultimately became standard questions and paradigms. The application of the then still novel hippocampal slice technique oriented LTP towards basic neuroscience, perhaps somewhat at the cost of lesser attention to its functional significance. The use of slices led to the discovery of the events that trigger the formation of LTP and provided some first clues about its extraordinary persistence.
1 Introduction
Authors: Dunn J Michael , Hardegree Gary M
Published: November 2023

The reader who is completely new to algebraic logic may find this the hardest chapter in the book, since it uses concepts that may not be adequately explained. Such a reader is advised to skim this chapter at first reading and then to read relevant parts again as appropriate concepts are mastered.
The multiplicity of logics
Authors: John P. Cleave
Published: November 2023

Logics, in the plural, are the subject of this book. Why should there be more than one logic?
Classical logic
Authors: John P. Cleave
Published: November 2023

For the established naive realist view permeating mathematics and science the classical two-valued logic is the logic, which is naturally and unquestionably supreme. Other conceptions of logic or mathematics are quaintly ideological; other people’s ideas are distinctly metaphysical. Nevertheless, the usually unspoken classical view is a definite philosophical stance whose metaphysical presuppositions are the legacy of history. Mathematical and logical truths are a reflection of an objective external structure--they are seen as analogous to a universe of clear-cut objects and relations between them essentially set apart from the knowing subject, the community, and institutions of mathematics and science. Truths, like supermarket commodities, are discovered, not invented. It is assumed that each well-formed formula of logic has one of the truth-values truth or falsehood independently of proof and the way in which it is determined (hence the Aristotelian principle of the excluded middle), i.e. it is truth-definite. This realist view was explicitly stated by the mathematician G. H. Hardy:
Logical operations
Authors: John P. Cleave
Published: November 2023

In the preceding chapter the notion of a logic was defined. A language Qf2, suitable for expressing conditions satisfied by logics, was defined. Various examples were given in Chapters 1 and 2. The present chapter is a taxonomic exercise—we define some important classes of logics axiomatically using logical operations as the principle of classification (for an algebraic treatment see Rasiowa (1974)). These axiomo/ are all expressible as simple definite program clauses and are therefore subject to the transfer theorems of Chapter 3, §3.4.
Three-valued logic
Authors: John P. Cleave
Published: November 2023

The main aim of this chapter is to study the logic of inexactness arising from Korner’s theory of inexact classes and predicates (Chapter 1, §1.3.2 and Chapter 7, §7.7). We first study logics whose truth-values are the QBA’s B2, N3, and Q4 (Chapter 7, Fig. 7.1). Though the centre of attention is N3, a completeness proof is given which is applicable in all three cases (§8.8).
Relevance
Authors: Cleave John P
Published: November 2023

In many of the standard formulations of the classical propositional calculus there are to found the theorems A ⊃ [B ⊃ A] and -7A ⊃ [,A ⊃ B]. The sense of the first is frequently expressed by saying that if a proposition is true then any proposition whatever implies it. The sense of the second is expressed by asserting that if a proposition is false then it implies any proposition. These theorems are often called the ‘paradoxes of (material) implication’. Certain related kinds of implication such as AA‘B and B ⟶ A v A’ are sometimes regarded as fallacious or paradoxical, even though classically correct, on the grounds that AA‘ (or A v A’) is irrelevant to the arbitrary proposition B. Much of the criticism of such implications has focused on the nature of disjunction.
The calculus of logics: effective logic
Authors: Cleave John P
Published: November 2023

The semantically based logics of previous chapters can be considered as the logics of particular sciences or formal systems. The task we now undertake is to regularize the discourse about logics: can a science of logics (Chapter 1, §1.2) be built?
The Theory of Transformation Groups
Authors: Kawakubo Katsuo
Published: November 2023

The aim of this book is to present an introduction to the theory of transformation groups which will be suitable for all those coming to the subject for the first time. The emphasis is on the study of topological groups and, in particular, the study of compact Lie groups acting on manifolds. Throughout, much care is taken to illustrate concepts and results with examples and applications. Numerous exercises are also included to further extend a reader's understanding and knowledge. Prerequisites are a familiarity with algebra and topology as might have been acquired from an undergraduate degree in Mathematics. The author begins by introducing the basic concepts of the subject such as fixed point sets, orbits, and induced transformation groups. Attention then turns to the study of differentiable manifolds and Lie groups with particular emphasis on fibre bundles and characteristic classes. The latter half of the book is devoted to surveying the main themes of the subject: structure and decomposition theorems, the existence and uniqueness theorems of principal orbits, transfer theorems, and the Lefschetz fixed point theorem.
Spheres of Radius 2 in Triangle Buildings. I
Authors: Tits Jacques
Published: November 2023

As on the picture, we shall always number 0, 1, 2 the three types of vertices of .6.. We denote by Verta (resp. Vert;.6.) the set of all vertices (resp. all vertices of type i) of a, and always suppose a to be thick, in which case all 1-simplices are contained in the same number of2-simplices (or chambers);We distinguish thoee two classes by means of an invariant taking its values in Z/2Z. Computing that invariant in the case of the four buildings obtained, after M. Ronan, by amalgamation of three Frobenius groups of order 21 (cf. [3], {5], {6]) enables us to show that those four buildings are pairwise nonisomorphic and that two of them are not classical, that is, are not isomorphic to affine buildings of groups of type A2over a locally compact local field (whereas the two others are known to be classical: cf. [1] and [21). The 44 buildings of order 8 obtained by amalgamation of three Frobenius groups of order 9 73 (cf. [6], 3.2) can be approached by similar (but considerably more involved) methods, as I hope to show in a forthcoming paper.