國立虎尾科技大學 |

Quantitative methods in environmental and climate research

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Quantitative methods in environmental and climate research/ edited by Michela Cameletti, Francesco Finazzi.
其他作者:	Cameletti, Michela.
出版者:	Cham :Springer International Publishing : : 2018.,
面頁冊數:	vii, 136 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Climatology - Congresses. - Research -
電子資源:	https://doi.org/10.1007/978-3-030-01584-8
ISBN:	9783030015848

Quantitative methods in environmental and climate research
Quantitative methods in environmental and climate research[electronic resource] /edited by Michela Cameletti, Francesco Finazzi. - Cham :Springer International Publishing :2018. - vii, 136 p. :ill., digital ;24 cm.

1 Fast Bayesian classification for disease mapping and the detection of disease clusters -- 2 A Novel Hierarchical Multinomial Approach to Modelling Age-specific Harvest Data -- 3 Detection of change points in spatiotemporal data in presence of outliers and heavy-tailed observations -- 4 Modelling spatiotemporal mismatch for Aerosol profiles -- 5 A SPATIOTEMPORAL APPROACH FOR PREDICTING WIND SPEED ALONG THE COAST OF VALPARAISO, CHILE -- 6 Spatiotemporal Precipitation Variability Modeling in the Blue Nile Basin: 1998-2016 -- 7 A hidden Markov random field with copula-based emission distributions for the analysis of spatial cylindrical data.

This books presents some of the most recent and advanced statistical methods used to analyse environmental and climate data, and addresses the spatial and spatio-temporal dimensions of the phenomena studied, the multivariate complexity of the data, and the necessity of considering uncertainty sources and propagation. The topics covered include: detecting disease clusters, analysing harvest data, change point detection in ground-level ozone concentration, modelling atmospheric aerosol profiles, predicting wind speed, precipitation prediction and analysing spatial cylindrical data. The volume presents revised versions of selected contributions submitted at the joint TIES-GRASPA 2017 Conference on Climate and Environment, which was held at the University of Bergamo, Italy. As it is chiefly intended for researchers working at the forefront of statistical research in environmental applications, readers should be familiar with the basic methods for analysing spatial and spatio-temporal data.

ISBN: 9783030015848

Standard No.: 10.1007/978-3-030-01584-8doiSubjects--Topical Terms:

1211859
Climatology
--Research--Congresses.

LC Class. No.: QC980 / .Q368 2018

Dewey Class. No.: 551.6

Quantitative methods in environmental and climate research
LDR:02645nam a2200325 a 4500 001 930598
003 DE-He213
005 20190513095720.0
006 m d
007 cr nn 008maaau
008 190627s2018 gw s 0 eng d
020 $a 9783030015848 $q (electronic bk.)
020 $a 9783030015831 $q (paper)
024 7 $a 10.1007/978-3-030-01584-8 $2 doi
035 $a 978-3-030-01584-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QC980 $b .Q368 2018
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 551.6 $2 23
090 $a QC980 $b .Q1 2018
245 0 0 $a Quantitative methods in environmental and climate research $h [electronic resource] / $c edited by Michela Cameletti, Francesco Finazzi.
260 $a Cham : $c 2018. $b Springer International Publishing : $b Imprint: Springer,
300 $a vii, 136 p. : $b ill., digital ; $c 24 cm.
505 0 $a 1 Fast Bayesian classification for disease mapping and the detection of disease clusters -- 2 A Novel Hierarchical Multinomial Approach to Modelling Age-specific Harvest Data -- 3 Detection of change points in spatiotemporal data in presence of outliers and heavy-tailed observations -- 4 Modelling spatiotemporal mismatch for Aerosol profiles -- 5 A SPATIOTEMPORAL APPROACH FOR PREDICTING WIND SPEED ALONG THE COAST OF VALPARAISO, CHILE -- 6 Spatiotemporal Precipitation Variability Modeling in the Blue Nile Basin: 1998-2016 -- 7 A hidden Markov random field with copula-based emission distributions for the analysis of spatial cylindrical data.
520 $a This books presents some of the most recent and advanced statistical methods used to analyse environmental and climate data, and addresses the spatial and spatio-temporal dimensions of the phenomena studied, the multivariate complexity of the data, and the necessity of considering uncertainty sources and propagation. The topics covered include: detecting disease clusters, analysing harvest data, change point detection in ground-level ozone concentration, modelling atmospheric aerosol profiles, predicting wind speed, precipitation prediction and analysing spatial cylindrical data. The volume presents revised versions of selected contributions submitted at the joint TIES-GRASPA 2017 Conference on Climate and Environment, which was held at the University of Bergamo, Italy. As it is chiefly intended for researchers working at the forefront of statistical research in environmental applications, readers should be familiar with the basic methods for analysing spatial and spatio-temporal data.
650 0 $a Climatology $x Research $v Congresses. $3 1211859
650 0 $a Ecology $x Research $v Congresses. $3 866579
650 1 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
650 2 4 $a Theoretical Ecology/Statistics. $3 678528
650 2 4 $a Climate Change. $3 668924
650 2 4 $a Statistical Theory and Methods. $3 671396
650 2 4 $a Climate Change/Climate Change Impacts. $3 1023634
650 2 4 $a Monitoring/Environmental Analysis. $3 1113426
700 1 $a Cameletti, Michela. $3 1163223
700 1 $a Finazzi, Francesco. $3 1211858
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-3-030-01584-8
950 $a Mathematics and Statistics (Springer-11649)