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E. H. Simpson

Bio: E. H. Simpson is an academic researcher. The author has contributed to research in topics: Devonian & Fluvial. The author has an hindex of 2, co-authored 3 publications receiving 10509 citations.

Papers
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Journal ArticleDOI
01 Jan 1949-Nature
TL;DR: In this article, the authors define and examine a measure of concentration in terms of population constants, and examine the relationship between the characteristic and the index of diversity when both are applied to a logarithmic distribution.
Abstract: THE 'characteristic' defined by Yule1 and the 'index of diversity' defined by Fisher2 are two measures of the degree of concentration or diversity achieved when the individuals of a population are classified into groups. Both are defined as statistics to be calculated from sample data and not in terms of population constants. The index of diversity has so far been used chiefly with the logarithmic distribution. It cannot be used everywhere, as it does not always give values which are independent of sample size ; it cannot do so, for example, when applied to an infinite population of individuals classified into a finite number of groups. Williams3 has pointed out a relationship between the characteristic and the index of diversity when both are applied to a logarithmic distribution. The present purpose is to define and examine a measure of concentration in terms of population constants.

10,077 citations

Journal ArticleDOI
27 Jan 2023-PALAIOS
TL;DR: In this article , a comparison of modern bird and dinosaur shells with modern bird shells, including some samples heated to diagenetic temperatures, indicate that the residue is degraded organic compounds (DOC).
Abstract: Abstract: Dinosaur eggshell fragments, from the Upper Jurassic Brushy Basin Member of the Morrison Formation, Utah, were examined using Field Emission Scanning Electron Microscope (FESEM), Energy Dispersive Spectroscopy, and Raman Spectroscopy. Analyses revealed that the mammillary tips on the shell interior contain carbonaceous residue. Comparison under the FESEM of these shells with modern bird shells, including some samples heated to diagenetic temperatures, indicate that the residue is degraded organic compounds (DOC). Bird egg membrane is composed of interlaced collagen fibers. Features observed on, and common to, modern bird and dinosaur egg fragments include: (1) irregular-shaped calcium carbonate grains “floating” in an organic matrix; (2) three-dimensional organic fiber matrix; (3) external calcium carbonate molds of fibers in the mammillary bodies; and in heated specimens, (4) carbonaceous residue with ovate to circular pores. However, unlike birds' eggs, the dinosaur eggs contain a calcium carbonate tube around fibrous organic material that emerges from the tube and spreads laterally in a ‘puddle-like’ deposit. The sizes of circular organic matrix pores of the dinosaur egg fragments are significantly smaller than those in the bird shells. Gallus gallus domesticus eggshell membranes heated to diagenetic temperatures resulted in alteration of collagen fibers to gel-like substances. The organic matrix with ovate to circular pore openings and the puddle-like deposits in the dinosaur egg fragments are interpreted as the product of membrane thermal diagenesis. The recognition of carbonaceous residue of the shell membrane on dinosaur shell fragments opens newfound opportunities to explore DOC associated with fragmental dinosaur eggs.
Journal ArticleDOI
TL;DR: This article used thicknesses of fluvial architectural elements within the Late Ordovician Taconic, the Late Devonian-Early Mississippian Acadian, and the Late Mississippians to Early and Middle Pennsylvanian Alleghanian clastic wedges, together with climatic conditions interpreted from palaeosol data, to estimate the drainage areas and discharges of the river systems which drained the hinterlands of the accreted taconic and Acadian terrains.
Abstract: Source‐to‐sink studies typically utilize the sedimentary record preserved in basins to infer source area parameters such as estimates of drainage area and discharges of fluvial systems in the hinterland, the characterization of which remains elusive as few geomorphic elements of the hinterland are preserved. Clastic wedges within foreland basin settings often contain fluvial deposits, and the scale of fluvial architectural elements can be used to estimate drainage area and discharge within the accreted hinterland. This study uses thicknesses of fluvial architectural elements within the Late Ordovician Taconic, the Late Devonian‐Early Mississippian Acadian, and the Late Mississippian to Early and Middle Pennsylvanian Alleghanian clastic wedges, together with climatic conditions interpreted from palaeosol data, to estimate the drainage areas and discharges of the river systems which drained the hinterlands of the accreted Taconic and Acadian terrains and the Alleghanian suture of Laurentia and Gondwana. Published detrital zircon age spectra provide insight into ages of source areas of sediments as well as the timing of terrane accretion. The increase in hinterland drainage areas calculated for Late Devonian Acadian Orogeny river systems compared to Late Ordovician Taconic Orogeny river systems can be attributed to the increase in size of accreted terranes to the east of the foreland basins during that period of time. The decrease in hinterland drainage area from the Late Devonian Acadian Orogeny to the Middle to Late Pennsylvanian Alleghanian Orogeny is attributed to the westward migration of the drainage divide as the Alleghanian orogeny proceeded. It is inferred that the drainage divide migrated towards the drier leeward side of the mountain range and caused drainage basins to shrink and split into smaller drainage basins.

Cited by
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Book
01 Jan 1983
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Abstract: The technique of iterative weighted linear regression can be used to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation. A generalization of the analysis of variance is given for these models using log- likelihoods. These generalized linear models are illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables) and gamma (variance components).

23,215 citations

Book
01 Jan 1988
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Abstract: From the Publisher: Probabilistic Reasoning in Intelligent Systems is a complete andaccessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty—and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition—in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

15,671 citations

Journal ArticleDOI
01 May 1972
TL;DR: In this paper, the authors used iterative weighted linear regression to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation.
Abstract: JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Blackwell Publishing and Royal Statistical Society are collaborating with JSTOR to digitize, preserve and extend access to Journal of the Royal Statistical Society. Series A (General). SUMMARY The technique of iterative weighted linear regression can be used to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation. A generalization of the analysis of variance is given for these models using log-likelihoods. These generalized linear models are illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables) and gamma (variance components). The implications of the approach in designing statistics courses are discussed.

8,793 citations

Journal ArticleDOI
01 May 1972-Taxon

4,445 citations

Journal ArticleDOI
18 Apr 1969-Science
TL;DR: The principles of ecological succession bear importantly on the relationships between man and nature and needs to be examined as a basis for resolving man’s present environmental crisis.
Abstract: The principles of ecological succession bear importantly on the relationships between man and nature. The framework of successional theory needs to be examined as a basis for resolving man’s present environmental crisis. Most ideas pertaining to the development of ecological systems are based on descriptive data obtained by observing changes in biotic communities over long periods, or on highly theoretical assumptions; very few of the generally accepted hypotheses have been tested experimentally. Some of the confusion, vagueness, and lack of experimental work in this area stems from the tendency of ecologists to regard “succession” as a single straightforward idea; in actual fact, it entails an interacting complex of processes, some of which counteract one another.

4,419 citations