Accuracy and Precision
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Data Types Are Values
Data Types Are Values James Donahue Alan Demers Data Types Are Values James Donahue Xerox Corporation Palo Alto Research Center 3333 Coyote Hill Road Palo Alto, California 94304 Alan Demers Computer Science Department Cornell University Ithaca, New York 14853 CSL -83-5 March 1984 [P83-00005] © Copyright 1984 ACM. All rights reserved. Reprinted with permission. A bst ract: An important goal of programming language research is to isolate the fundamental concepts of languages, those basic ideas that allow us to understand the relationship among various language features. This paper examines one of these underlying notions, data type, with particular attention to the treatment of generic or polymorphic procedures and static type-checking. A version of this paper will appear in the ACM Transact~ons on Programming Languages and Systems. CR Categories and Subject Descriptors: 0.3 (Programming Languages), 0.3.1 (Formal Definitions and Theory), 0.3.3 (Language Constructs), F.3.2 (Semantics of Programming Languages) Additional Keywords and Phrases: data types, polymorphism XEROX Xerox Corporation Palo Alto Research Center 3333 Coyote Hill Road Palo Alto, California 94304 DATA TYPES ARE VALVES 1 1. Introduction An important goal of programming language research is to isolate the fundamental concepts of languages, those basic ideas that allow us to understand the relationship among various language features. This paper examines one of these underlying notions, data type, and presents a meaning for this term that allows us to: describe a simple treatment of generic or polymorphic procedures that preserves full static type-checking and allows unrestricted use of recursion; and give a precise meaning to the phrase strong typing, so that Language X is strongly typed can be interpreted as a critically important theorem about the semantics of the language. -
Reliability” Within the Qualitative Methodological Literature As a Proxy for the Concept of “Error” Within the Qualitative Research Domain
The “Error” in Psychology: An Analysis of Quantitative and Qualitative Approaches in the Pursuit of Accuracy by Donna Tafreshi MA, Simon Fraser University, 2014 BA, Simon Fraser University, 2011 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Department of Psychology Faculty of Arts and Social Sciences © Donna Tafreshi 2018 SIMON FRASER UNIVERSITY Fall 2018 Copyright in this work rests with the author. Please ensure that any reproduction or re-use is done in accordance with the relevant national copyright legislation. Approval Name: Donna Tafreshi Degree: Doctor of Philosophy Title: The “Error” in Psychology: An Analysis of Quantitative and Qualitative Approaches in the Pursuit of Accuracy Examining Committee: Chair: Thomas Spalek Professor Kathleen Slaney Senior Supervisor Professor Timothy Racine Supervisor Professor Susan O’Neill Supervisor Professor Barbara Mitchell Internal Examiner Professor Departments of Sociology & Gerontology Christopher Green External Examiner Professor Department of Psychology York University Date Defended/Approved: October 12, 2018 ii Abstract The concept of “error” is central to the development and use of statistical tools in psychology. Yet, little work has focused on elucidating its conceptual meanings and the potential implications for research practice. I explore the emergence of uses of the “error” concept within the field of psychology through a historical mapping of its uses from early observational astronomy, to the study of social statistics, and subsequently to its adoption under 20th century psychometrics. In so doing, I consider the philosophical foundations on which the concepts “error” and “true score” are built and the relevance of these foundations for its usages in psychology. -
Governing Collective Action in the Face of Observational Error
Governing Collective Action in the Face of Observational Error Thomas Markussen, Louis Putterman and Liangjun Wang* August 2017 Abstract: We present results from a repeated public goods experiment where subjects choose by vote one of two sanctioning schemes: peer-to-peer (informal) or centralized (formal). We introduce, in some treatments, a moderate amount of noise (a 10 percent probability that a contribution is reported incorrectly) affecting either one or both sanctioning environments. We find that the institution with more accurate information is always by far the most popular, but noisy information undermines the popularity of peer-to-peer sanctions more strongly than that of centralized sanctions. This may contribute to explaining the greater reliance on centralized sanctioning institutions in complex environments. JEL codes: H41, C92, D02 Keywords: Public goods, sanctions, information, institution, voting * University of Copenhagen, Brown University, and Zhejiang University of Technology, respectively. We would like to thank The National Natural Science Foundation of China (Grant No.71473225) and The Danish Council for Independent Research (DFF|FSE) for funding. We thank Xinyi Zhang for assistance in checking translation of instructions, and Vicky Zhang and Kristin Petersmann for help in checking of proofs. We are grateful to seminar participants at University of Copenhagen, at the Seventh Biennial Social Dilemmas Conference held at University of Massachusetts, Amherst in June 2017, and to Attila Ambrus, Laura Gee and James Walker for helpful comments. 1 Introduction When and why do groups establish centralized, formal authorities to solve collective action problems? This fundamental question was central to classical social contract theory (Hobbes, Locke) and has recently been the subject of a group of experimental studies (Okada, Kosfeld and Riedl 2009, Traulsen et al. -
The Role of Observational Errors in Optimum Interpolation Analysis :I0
U.S. DEPARTMENT OF COMMERCE NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION NATIONAL WEATHER SERVICE NATIONAL METEOROLOGICAL CENTER OFFICE NOTE 175 The Role of Observational Errors in Optimum Interpolation Analysis :I0. K. H. Bergman Development Division APRIL 1978 This is an unreviewed manuscript, primarily intended for informal exchange of information among NMC staff members. k Iil The Role of Observational Errors in Optimum Interpolation Analysis 1. Introduction With the advent of new observing systems and the approach of the First GARP Global Experiment (FGGE), it appears desirable for data providers to have some knowledge of how their product is to be used in the statistical "optimum interpolation" analysis schemes which will operate at most of the Level III centers during FGGE. It is the hope of the author that this paper will serve as a source of information on the way observational data is handled by optimum interpolation analysis schemes. The theory of optimum interpolation analysis, especially with regard to the role of observational errors, is reviewed in Section 2. In Section 3, some comments about determining observational error characteristics are given along with examples of same. Section 4 discusses error-checking procedures which are used to identify suspect observations. These latter procedures are an integral part of any analysis scheme. 2. Optimum Interpolation Analysis The job of the analyst is to take an irregular distribution of obser- vations of variable quality and obtain the best possible estimate of a meteorological field at a regular network of grid points. The optimum interpolation analysis scheme attempts to accomplish this goal by mini- mizing the mean square interpolation error for a large ensemble of analysis situations. -
Ignificant Scientific Progress Is Increasingly the Result of National Or Confine Hot Plasma
ADVERTISEMENT FEATURE LIGHTING THE WAY FOR TOMORROW ignificant scientific progress is increasingly the result of national or confine hot plasma. Its maximum repeatable plasma current can reach 1MA, S international collaboration. A particular strength of the University currently the highest in the world, while its diverted plasma discharge is the of Science and Technology of China (USTC) is its powerful facilities world’s longest. designed specifically to cater for large-scale science, which will help form In 2017, EAST achieved more than 100 seconds of steady-state, the bedrock of China’s second Comprehensive National Science Center, high-confinement mode (H-mode) operation, a world record. This has based in Hefei. implications for the International Thermonuclear Experimental Reactor (ITER), a huge international effort, in which China is a participant, aiming to Accelerating research with the Hefei Light Source build the infrastructure to provide clean nuclear fusion power. USTC has proven expertise in major national projects. With USTC’s support, International collaborations through EAST have already included a joint China’s synchrotron radiation accelerator was officially launched in 1983, experiment on steady-state operation with the DIII-D team of defence becoming the country’s first dedicated VUV and soft X-ray synchrotron contractor General Atomics in the United States, joint conferences and radiation facility — the Hefei Light Source (HLS). projects on plasma-wall interactions with Germany, and joint efforts with To better serve growing demand, phase II of the HLS (HLS-II) was Russia to translate research results. launched in 2010. In this phase a linear accelerator, an 800MeV storage ring and five beamline stations were built, all of which, plus the top-off operation More fusion power: Keda Torus eXperiment mode, have significantly improved the stability, brightness and service life Another device harnessing fusion power is USTC’s Keda Torus eXperiment of the light source. -
Monthly Weather Review James E
DEPARTMENT OF COMMERCE WEATHERBUREAU SINCLAIR WEEKS, Secretary F. W. REICHELDERFER, Chief MONTHLY WEATHER REVIEW JAMES E. CASKEY, JR., Editor Volume 83 Cloeed Febru 15, 1956 Number 12 DECEMBER 1955 Issued Mm% 15, 1956 A SIMULTANEOUS LAGRANGIAN-EULERIAN TURBULENCE EXPERIMENT F'RA.NK GIFFORD, R. U. S. Weather Bureau The Pennsylvania State University * [Manuscript received October 28, 1955; revised January 9, 1956J ABSTRACT Simultaneous measurements of turbulent vertical velocity fluctuationsat a height of 300 ft. measured by means of a fixed anemometer, small floating balloons, and airplane gust equipment at Brookhaven are presented. The re- sulting Eulerian (fixed anemometer) turbulence energy mectra are similar to the Lagrangian (balloon) spectra but " - with a displacement toward higher frequencies. 1. THE NATURE OF THEPROBLEM function, and the closely related autocorrelation function. This paper reports an attempt to make measurements of The term Eulerian, in turbulence study, impliescon- both Lagrangian and Eulerianturbulence fluctuations sideration of velocity fluctuations at a point or points simultaneously. This problem owes its importance largely fixed in space, as measured for example by one or more to the fact that experimenters usually measure the Eu- fixed anemometers or wind vanes. The term Lagrangian lerian-time form of the turbulence spectrumor correlation, implies study of the fluctuations of individual fluid par- which all 6xed measuring devices of turbulence record; cels; these are very difficult to measure. In a sense, these but theoretical developments as well as practical applica- two points of view of the turbulence phenomenon are tionsinevitably require the Eulerian-space, or the La- closely related tothe two most palpable physical manifesta- grangian form. -
Figureseer: Parsing Result-Figures in Research Papers
FigureSeer: Parsing Result-Figures in Research Papers Noah Siegel, Zachary Horvitz, Roie Levin, Santosh Divvala, and Ali Farhadi Allen Institute for Artificial Intelligence University of Washington http://allenai.org/plato/figureseer Fig. 1: FigureSeer is an end-to-end framework for parsing result-figures in research papers. It automatically localizes figures, classifies them, and analyses their content (center). FigureSeer enables detailed indexing, retrieval, and redesign of result-figures, such as highlighting specific results (top-left), reformatting results (bottom-left), com- plex query answering (top-right), and results summarization (bottom-right). Abstract. `Which are the pedestrian detectors that yield a precision above 95% at 25% recall?' Answering such a complex query involves identifying and analyzing the results reported in figures within several research papers. Despite the availability of excellent academic search en- gines, retrieving such information poses a cumbersome challenge today as these systems have primarily focused on understanding the text content of scholarly documents. In this paper, we introduce FigureSeer, an end- to-end framework for parsing result-figures, that enables powerful search and retrieval of results in research papers. Our proposed approach au- tomatically localizes figures from research papers, classifies them, and analyses the content of the result-figures. The key challenge in analyzing the figure content is the extraction of the plotted data and its association with the legend entries. We address this challenge by formulating a novel graph-based reasoning approach using a CNN-based similarity metric. We present a thorough evaluation on a real-word annotated dataset to demonstrate the efficacy of our approach. 1 Computer Vision for Scholarly Big Data Academic research is flourishing at an unprecedented pace. -
Arxiv:2103.01707V1 [Astro-Ph.EP] 2 Mar 2021
Draft version March 3, 2021 Typeset using LATEX preprint2 style in AASTeX63 Mass and density of asteroid (16) Psyche Lauri Siltala1 and Mikael Granvik1, 2 1Department of Physics, P.O. Box 64, FI-00014 University of Helsinki, Finland 2Asteroid Engineering Laboratory, Onboard Space Systems, Lule˚aUniversity of Technology, Box 848, S-98128 Kiruna, Sweden (Received October 1, 2020; Revised February 23, 2021; Accepted February 23, 2021) Submitted to ApJL ABSTRACT We apply our novel Markov-chain Monte Carlo (MCMC)-based algorithm for asteroid mass estimation to asteroid (16) Psyche, the target of NASA's eponymous Psyche mission, based on close encounters with 10 different asteroids, and obtain a mass of −11 (1:117 0:039) 10 M . We ensure that our method works as expected by applying ± × it to asteroids (1) Ceres and (4) Vesta, and find that the results are in agreement with the very accurate mass estimates for these bodies obtained by the Dawn mission. We then combine our mass estimate for Psyche with the most recent volume estimate to compute the corresponding bulk density as (3:88 0:25) g/cm3. The estimated ± bulk density rules out the possibility of Psyche being an exposed, solid iron core of a protoplanet, but is fully consistent with the recent hypothesis that ferrovolcanism would have occurred on Psyche. Keywords: to be | added later 1. INTRODUCTION and radar observations (Shepard et al. 2017). Asteroid (16) Psyche is currently of great in- There have, however, been concerns that Psy- terest to the planetary science community as che's relatively high bulk density of approxi- 3 it is the target of NASA's eponymous Psyche mately 4 g/cm is still too low to be consis- mission currently scheduled to be launched in tent with iron meteorites and that the asteroid 2022 (Elkins-Tanton et al. -
Error Statistics of Asteroid Optical Astrometric Observations
Icarus 166 (2003) 248–270 www.elsevier.com/locate/icarus Error statistics of asteroid optical astrometric observations Mario Carpino,a,∗ Andrea Milani,b andStevenR.Chesleyc a Osservatorio Astronomico di Brera, via Brera, 28, 20121 Milan, Italy b Dipartimento di Matematica, Università di Pisa, Via Buonarroti, 2, 56127 Pisa, Italy c Navigation & Mission Design Section, MS 301-150, Jet Propulsion Laboratory, Pasadena, CA 91109, USA Received 29 May 2001; revised 25 October 2002 Abstract Astrometric uncertainty is a crucial component of the asteroid orbit determination process. However, in the absence of rigorous uncer- tainty information, only very crude weighting schemes are available to the orbit computer. This inevitably leads to a correspondingly crude characterization of the orbital uncertainty and in many cases to less accurate orbits. In this paper we describe a method for carefully assessing the statistical performance of the various observatories that have produced asteroid astrometry, with the ultimate goal of using this statistical characterization to improve asteroid orbit determination. We also include a detailed description of our previously unpublished automatic outlier rejection algorithm used in the orbit determination, which is an important component of the fitting process. To start this study we have determined the best fitting orbits for the first 17,349 numbered asteroids and computed the corresponding O–C astrometric residuals for all observations used in the orbit fitting. We group the residuals into roughly homogeneous bins and compute the root mean square (RMS) error and bias in declination and right ascension for each bin. Results are tabulated for each of the 77 bins containing more than 3000 observations; this comprises roughly two thirds of the data, but only 2% of the bins. -
Artificial Intelligence for Marketing: Practical Applications, Jim Sterne © 2017 by Rising Media, Inc
Trim Size: 6in x 9in k Sterne ffirs.tex V1 - 07/19/2017 7:25am Page i Artificial Intelligence for Marketing k k k Trim Size: 6in x 9in k Sterne ffirs.tex V1 - 07/19/2017 7:25am Page ii Wiley & SAS Business Series The Wiley & SAS Business Series presents books that help senior-level managers with their critical management decisions. Titles in the Wiley & SAS Business Series include: Analytics in a Big Data World: The Essential Guide to Data Science and Its Applications by Bart Baesens A Practical Guide to Analytics for Governments: Using Big Data for Good by Marie Lowman Bank Fraud: Using Technology to Combat Losses by Revathi Subramanian Big Data Analytics: Turning Big Data into Big Money by Frank Ohlhorst Big Data, Big Innovation: Enabling Competitive Differentiation through by Evan Stubbs k Business Analytics k Business Analytics for Customer Intelligence by Gert Laursen Business Intelligence Applied: Implementing an Effective Information and Communications Technology Infrastructure by Michael Gendron Business Intelligence and the Cloud: Strategic Implementation Guide by Michael S. Gendron Business Transformation: A Roadmap for Maximizing Organizational Insights by Aiman Zeid Connecting Organizational Silos: Taking Knowledge Flow Management to the Next Level with Social Media by Frank Leistner Data-Driven Healthcare: How Analytics and BI Are Transforming the Industry by Laura Madsen Delivering Business Analytics: Practical Guidelines for Best Practice by Evan Stubbs Demand-Driven Forecasting: A Structured Approach to Forecasting, Second -
Observational Error Covariance Specification in Ensemble Based
Observational error covariance specification in ensemble based Kalman filter algorithms Tijana Janji´c1, Alberta Albertella2,Sergey Skachko3, Jens Schr¨oter1, Rein- hard Rummel2 1 Alfred Wegener Institute, Germany [email protected], 2 Institute for Astronomical and Physical Geodesy, TU Munich, Germany, 3 Department of Earth Sciences, University of Quebec in Montreal, Canada 1 Introduction The analysis for each water column of the model depends only The weighting by 5th order polynomial shows almost evenly dis- on observations within a specified influence region. Thirteen tributed error structures for all scales. Note that since data itself The study focuses on the effects of different observational error ensemble members are used in the implementation of the local have spectral coefficients only up to order 35, everything above 35 covariance structures on the assimilation in ensemble based SEIK algorithm. Observational error variance was set to 25 cm2. is the error that was introduced by analysis scheme and further Kalman filter with domain localization. With the domain amplified by the forecast. For the two weighting results shown localization methods, disjoint domains in the physical space this error is quite small. are considered as domains on which the analysis is performed. 4 Effects on accuracy of weighting of Therefore, for each subdomain an analysis step is performed observations independently using observations not necessarily belonging only to that subdomain. Results of the analysis local steps are pasted The two correlation models used are plotted in Fig. 4 and together and then the global forecast step is performed. compared to uniform weighting. The use of correlation models improves the accuracy of forecast compared to uniform weight- The method of observational error covariance localization ing (figure not shown here). -
Artefact Corrections in Meta-Analysis
Postprint Advances in Methods and Practices in Psychological Science XX–XX Obtaining Unbiased Results in © The Author(s) 2019 Not the version of record. Meta-Analysis: The Importance of The version of record is available at DOI: XXX www.psychologicalscience.org/AMPPS Correcting for Statistical Artefacts Brenton M. Wiernik1 and Jeffrey A. Dahlke2 1Department of Psychology, University of South Florida, Tampa, FL, USA 2Human Resources Research Organization, Alexandria, VA, USA Abstract Most published meta-analyses address only artefactual variance due to sampling error and ignore the role of other statistical and psychometric artefacts, such as measurement error (due to factors including unreliability of meas- urements, group misclassification, and variable treatment strength) and selection effects (including range restriction/enhancement and collider biases). These artefacts can have severe biasing effects on the results of individual studies and meta-analyses. Failing to account for these artefacts can lead to inaccurate conclusions about the mean effect size and between-studies effect-size heterogeneity, and can influence the results of meta-regression, publication bias, and sensitivity analyses. In this paper, we provide a brief introduction to the biasing effects of measurement error and selection effects and their relevance to a variety of research designs. We describe how to estimate the effects of these artefacts in different research designs and correct for their impacts in primary studies and meta-analyses. We consider meta-analyses