News&Info
Your CoDa-news are very welcomed! contribute to this section!
To do this please send to webmaster@coda-association.org the following information:
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20.03.2020Council agreement for Electoral Commission
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20.03.2020
CoDa Association grants for the Week‐CoDaCourse 2020
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02.02.2020
Invited session on compositional data analysis at ERCIM 2020 – call for papers
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19.01.2020
New Meetings Committee!
The Council of the CoDa Association appoints a Meetings Committee
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25.11.2019
Session on Compositional data analysis
Joint ISEH 2020, ICEPH 2020 & G16 2020 conference
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28.10.2019
Week-CoDaCourse at UdG
9th Course and Open Seminar on Compositional Data Analysis; 2020 July, 6-10; University of Girona
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15.10.2019
CoDa-thesis at TSE (Toulouse, France)
Contribution to the statistical analysis of compositional data with an application to political economy
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10.07.2019
CoDa-thesis at UdG (GIrona, Spain)
CONDITION ASSESSMENT OF PATIENTS WITH TYPE 1 DIABETES USING COMPOSITIONAl DATA ANALYSIS
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12.06.2019
CoDa-Keynote lectures at IAMG 2019
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12.06.2019
CoDa-session at IGC 2020 (India)
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21.02.2019
IAMG: Matheron Lecturer 2019
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14.01.2019
Presentation of the guest CoDa-article of the journal SORT
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10.01.2019
CoDa-book: Compositional Data Analysis in Practice
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10.01.2019
CoDa-book: Applied Compositional Data Analysis
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10.12.2018
Introductory Online Course on Compositional Analysis
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05.12.2018
CoDa-session at IAMG2019 !
State College, Pennsylvania, USA, 10−16 August 2019.
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30.10.2018
CoDa-thesis at UdG (Spain)
Mixture Models Contributions from Compositional Analysis
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26.09.2018
Special Issue on Compositional Data Analysis at the Austrian Journal of Statistics
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26.07.2018
Request for Proposals to Host CoDaWork2021
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17.07.2018
CoDaWork 2019
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17.05.2018
CARME 2019
Correspondence Analysis and Related Methods
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09.01.2018
7th CoDaCourse at UdG!
7th Course and Open Seminar on Compositional Data Analysis at UdG
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30.11.2017
New Meeting Committee
The CoDa-Association establish the Meeting Committee
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22.11.2017
CoDa-thesis
Impact of media investments on brands’ market shares: a compositional data analysis approach
