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Books on the topic 'Computer intensive methods'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Härdle, Wolfgang, and Léopold Simar, eds. Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4.

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2

Noreen, Eric W. Computer-intensive methods for testing hypotheses: An introduction. Wiley, 1989.

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3

Kárný, Miroslav, and Kevin Warwick, eds. Computer Intensive Methods in Control and Signal Processing. Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-1996-5.

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4

Rieder, Helmut, ed. Robust Statistics, Data Analysis, and Computer Intensive Methods. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2380-1.

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5

Computer intensive statistical methods: Validation model selection and bootstrap. Chapman & Hall, 1994.

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6

Kárný, Miroslav. Computer Intensive Methods in Control and Signal Processing: The Curse of Dimensionality. Birkhäuser Boston, 1997.

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7

Belarus) International Conference "Computer Data Analysis and Modeling" (6th 2001 Minsk. Computer data analysis and modeling: Robustness and computer intensive methods : proceedings of the sixth international conference, September 10-14, 2001, Minsk. Belararusian State University, 2001.

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8

International Workshop on Computationally Intensive Methods in Simulation and Optimization (1990 International Institute for Applied Systems Analysis). Simulation and optimization: Proceedings of the International Workshop on Computationally Intensive Methods in Simulation and Optimization, held at the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria, August 23-25,1990. Springer-Verlag, 1992.

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9

Hjorth, J. S. Urban. Computer Intensive Statistical Methods. Routledge, 2017. http://dx.doi.org/10.1201/9781315140056.

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10

Härdle, Wolfgang, and Léopold Simar. Computer Intensive Methods in Statistics. Physica, 2014.

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11

Wolfgang, Härdle, and Simar Léopold, eds. Computer intensive methods in statistics. Physica- Verlag, 1993.

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12

Zwanzig, Silvelyn, and Behrang Mahjani. Computer Intensive Methods in Statistics. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429202322.

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13

Hardle, Wolfgang. Computer Intensive Methods in Statistics (Statistics and Computing). Springer-Verlag, 1994.

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14

Warwick, Kevin, and Miroslav Karny. Computer-Intensive Methods in Control and Signal Processing. Springer, 2012.

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15

Finite Mixture Models : Review, Applications, and Computer-intensive Methods. University of Groningen, 2004.

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16

Hjorth, J. S. Urban. Computer Intensive Statistical Methods: Validation, Model Selection, and Bootstrap. Chapman & Hall/CRC, 1993.

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17

F, Tiako Pierre, ed. Designing software-intensive systems: Methods and principles. Information Science Reference, 2008.

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18

Introduction to Computer-Intensive Methods of Data Analysis in Biology. Cambridge University Press, 2006.

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19

Roff, Derek A. Introduction to Computer-Intensive Methods of Data Analysis in Biology. Cambridge University Press, 2006.

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20

K, Warwick, Kárný M, and European IEEE Workshop on Computer-Intensive Methods in Control and Signal Processing: Can We Beat the Curse of Dimensionality? (2nd : 1996 : Prague, Czech Republic), eds. Computer-intensive methods in control and signal processing: The curse of dimensionality. Birkhäuser, 1997.

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21

Warwick, Kevin, and Miroslav Karny. Computer Intensive Methods in Control and Signal Processing:: The Curse of Dimensionality. Birkhauser, 1997.

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22

J, Huber Peter, and Rieder Helmut, eds. Robust statistics, data analysis, and computer intensive methods: In honor of Peter Huber's 60th birthday. Springer, 1996.

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23

Mathematica Laboratories for Mathematical Statistics: Emphasizing Simulation and Computer Intensive Methods (ASA-SIAM Series on Statistics and Applied Probability). Society for Industrial and Applied Mathematic, 2004.

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24

Rieder, Helmut. Robust Statistics, Data Analysis, and Computer Intensive Methods: In Honor of Peter Huber's 60th Birthday (Lecture Notes in Statistics). Springer, 1996.

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25

Computer-intensive methods in control and signal processing: Preprints of the European IEEE Workshop CMP'94 : Prague, Czech Republic, September 7-9, 1994. Institute of Information Theory and Automation, 1994.

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26

Haig, Brian D. Exploratory Data Analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190222055.003.0002.

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Chapter 2 is concerned with modern data analysis. It focuses primarily on the nature, role, and importance of exploratory data analysis, although it gives some attention to computer-intensive resampling methods. Exploratory data analysis is a process in which data are examined to reveal potential patterns of interest. However, the use of traditional confirmatory methods in data analysis remains the dominant practice. Different perspectives on data analysis, as they are shaped by four different accounts of scientific method, are provided. A brief discussion of John Tukey’s philosophy of teachin

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27

Sutter, Raoul, Peter W. Kaplan, and Donald L. Schomer. Historical Aspects of Electroencephalography. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0001.

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Electroencephalography (EEG), a dynamic real-time recording of electrical neocortical brain activity, began in the 1600s with the discovery of electrical phenomena and the concept of an “action current.” The galvanometer was introduced in the 1800s and the first bioelectrical observations of human brain signals were made in the 1900s. Certain EEG patterns were associated with brain disorders, increasing the clinical and scientific use of EEG. In the 1980s, technical advances allowed EEGs to be digitized and linked with videotape recording. In the 1990s, digital data storage increased and compu

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28

Henderson, Daniel A., R. J. Boys, Carole J. Proctor, and Darren J. Wilkinson. Linking systems biology models to data: A stochastic kinetic model of p53 oscillations. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.7.

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This article discusses the use of a stochastic kinetic model to study protein level oscillations in single living cancer cells, using the p53 and Mdm2 proteins as examples. It describes the refinement of a dynamic stochastic process model of the cellular response to DNA damage and compares this model to time course data on the levels of p53 and Mdm2. The article first provides a biological background on p53 and Mdm2 before explaining how the stochastic kinetic model is constructed. It then introduces the stochastic kinetic model and links it to the data and goes on to apply sophisticated MCMC

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29

Torgerson,, Paul R., C. N. L. Macpherson, and D. A. Vuitton. Cystic echinococcosis. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780198570028.003.0060.

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Cystic echinococcosis (CE)\cystic hydatid disease is one of the most widespread and important global helminth zoonoses. The parasite Echinococcus granulosus is maintained in a wide spectrum of intermediate hosts, including sheep, goats, camels, cattle, pigs and equines. A number of wild intermediate hosts occur, including cervids in the northern part of the North American continent and Eurasia, marsupials in Australia and wild herbivores in East and southern Africa. The application of a range of molecular techniques to the characterization of the parasite has confirmed the existence of mostly

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30

Skiba, Grzegorz. Fizjologiczne, żywieniowe i genetyczne uwarunkowania właściwości kości rosnących świń. The Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences, 2020. http://dx.doi.org/10.22358/mono_gs_2020.

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Bones are multifunctional passive organs of movement that supports soft tissue and directly attached muscles. They also protect internal organs and are a reserve of calcium, phosphorus and magnesium. Each bone is covered with periosteum, and the adjacent bone surfaces are covered by articular cartilage. Histologically, the bone is an organ composed of many different tissues. The main component is bone tissue (cortical and spongy) composed of a set of bone cells and intercellular substance (mineral and organic), it also contains fat, hematopoietic (bone marrow) and cartilaginous tissue. Bones a

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