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Books on the topic 'Multivariate pattern analyses'

Author: Grafiati

Published: 10 December 2022

Last updated: 31 July 2025

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1

Bartlett, Sheryl Anne. Predictive and posterior distributions for normal multivariate data with missing monotone patterns. University of Toronto, Dept. of Statistics, 1985.

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2

G, Brereton Richard, ed. Multivariate pattern recognition in chemometrics: Illustrated by case studies. New York, 1992.

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3

E, Diday, and Brito Paula, eds. Selected contributions in data analysis and classification. Springer, 2007.

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4

Desikachar, Padmini. Patterns of labour market insecurity in rural India: A multidimensional and multivariate analysis. Madras School of Economics, 2011.

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5

Bock, Hans-Hermann. Advances in Multivariate Data Analysis: Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Palermo, July 5-6, 2001. Springer Berlin Heidelberg, 2004.

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6

I, Broeckaert, ed. Potential pattern recognition in chemical and medical decision making. Research Studies, 1986.

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7

I, Broeckaert, ed. Potential pattern recognition in chemical and medical decision making. Research Studies Press, 1986.

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8

International Federation of Classification Societies. Conference. Advances in data science and classification: Proceedings of the 6th Conference of the International Federation of Classification Societies (IFCS-98), Università "La Sapienza", Rome, 21-24 July, 1998. Springer, 1998.

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9

Hurdle, Sylvia. Factors underlying changes in physician productivity: Deliverable 5C (3) : final productivity report : updating and refinement of the health professions requirement model. Health Economics Research, Inc., 1986.

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10

LVA/ICA 2010 (2010 Saint-Malo, France). Latent variable analysis and signal separation: 9th international conference, LVA/ICA 2010, St. Malo, France, September 27-30, 2010 : proceedings. Springer, 2010.

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11

Sáiz, Francisco Javier Marcos. La Sierra de Atapuerca y el Valle del Arlanzón. Patrones de asentamiento prehistóricos. Editorial Dossoles, 2006.

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12

Saiz, Francisco Javier Marcos. La Prehistoria Reciente del entorno de la Sierra de Atapuerca (Burgos, España):: Catálogo de sitios del VI al II milenio cal. BC, análisis tecno-tipológico de las industrias líticas y cerámicas, y organización funcional del poblamiento. British Archaeological Reports, 2016.

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13

Pattern Recognition Analysis Via Genetic Algorithms & Multivariate Statistical Methods. CRC, 2001.

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14

Brereton, R. G. Multivariate Pattern Recognition in Chemometrics: Illustrated by Case Studies. Elsevier Science & Technology Books, 1992.

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15

Diggle, Peter J. Statistical Analysis of Spatial Point Patterns. 2nd ed. A Hodder Arnold Publication, 2003.

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16

D, László Orlóci Ph. Statistical multiscaling in dynamic ecology: Probing the long-term vegetation process for patterns of parameter oscillation. CreateSpace Independent Publishing Platform, 2012.

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17

Proceedings of the third annual Symposium on Mathematical Pattern Recognition & Image Analysis: June 10-11, 1985, Texas A & M University, College Station, Texas. Earth Resources Research Division, NASA/Johnson Space Center, 1985.

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18

Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning (Springer Texts in Statistics). Springer, 2009.

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19

Rainville, Pierre. A signature of pain in the brain. Edited by Paul Farquhar-Smith, Pierre Beaulieu, and Sian Jagger. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198834359.003.0029.

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The discovery of pain biomarkers has profound implications for both pharmacology and neurobiology; in 2013, in the landmark paper discussed in this chapter, Wager et al. presented a neurologic signature of pain based on human brain imaging performed in healthy individuals administered experimental heat-pain stimuli. Using advanced analytic methods based on machine learning and multivariate pattern analysis, Wagner et al. provide very convincing support for the idea that pain is encoded in a distinctive pattern of brain activity in one or several brain areas typically referred to as the ‘pain m

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20

Congendo, Marco, and Fernando H. Lopes da Silva. Event-Related Potentials. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0039.

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Event-related potentials (ERPs) can be elicited by a variety of stimuli and events in diverse conditions. This chapter covers the methodology of analyzing and quantifying ERPs in general. Basic models (additive, phase modulation and resetting, potential asymmetry) that account for the generation of ERPs are discussed. The principles and requirements of ensemble time averaging are presented, along with several univariate and multivariate methods that have been proposed to improve the averaging procedure: wavelet decomposition and denoising, spatial, temporal and spatio-temporal filtering. We em

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21

(Editor), Vladimir Batagelj, Hans-Hermann Bock (Editor), Anuska Ferligoj (Editor), and Ales Ziberna (Editor), eds. Data Science and Classification (Studies in Classification, Data Analysis, and Knowledge Organization). Springer, 2006.

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22

Bock, Hans Hermann, Alfredo Rizzi, and Maurizio Vichi. Advances in Data Science and Classification: Proceedings of the 6th Conference of the International Federation of Classification Societies (Ifcs-98) Universita ... Data Analysis, and Knowledge Organization). Springer-Verlag Telos, 1999.

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23

Bock, Hans Hermann, Alfredo Rizzi, and Maurizio Vichi. Advances in Data Science and Classification: Proceedings of the 6th Conference of the International Federation of Classification Societies Università la Sapienza , Rome, 21-24 July 1998. Springer London, Limited, 2013.

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24

Recent advances in functional data analysis and related topics. Physica-Verlag, 2011.

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25

Ferraty, Frédéric. Recent Advances in Functional Data Analysis and Related Topics. Springer, 2011.

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26

Mott IV, William H. United States Military Assistance. Praeger, 2002. http://dx.doi.org/10.5040/9798216030584.

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This interdisciplinary study examines the relationships between the provision of military assistance and success in achieving donor aims in history and theory, based upon an initial proposition that the relationship between donor and recipient is a critical determinant of success or failure. Mott builds upon his previous research of general historical and Soviet case studies which focuses on four initial features of the wartime donor-recipient relationship: convergence of aims; donor control, commitment of donor military forces, and coherence of donor policies and strategies. To this foundatio

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