Utvidet returrett til 31. januar 2024

Multivariate Time Series Analysis and Applications

Om Multivariate Time Series Analysis and Applications

Due to highΓÇôspeed internet and the power and speed of the new generation of computers, a researcher now faces somevery challenging phenomena and must deal with an everΓÇôincreasing amount of data. In order to find useful information and hidden patterns underlying the data, a researcher may use various dataΓÇômining methods and techniques for random samples. Adding a time dimension to these large databases certainly introduces new aspects and challenges. Following on from his highly successful and much lauded book, Time Series AnalysisΓÇôUnivariate and Multivariate Methods, this new work focuses is on high dimensional multivariate time series, illustrated with many high dimensional empirical time series. Multivariate Time Series Analysis and its Applications includes many topics that are not found in general multivariate time series books: repeated measurements space time series modelling dimension reduction This book is designed for an advanced time series analysis course, where researchΓÇôoriented projects will be suggested rather than introductory topics covered. It is a mustΓÇôhave for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9781119502852
  • Bindende:
  • Hardback
  • Sider:
  • 536
  • Utgitt:
  • 15. mars 2019
  • Dimensjoner:
  • 250x177x35 mm.
  • Vekt:
  • 1040 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 30. november 2024

Beskrivelse av Multivariate Time Series Analysis and Applications

Due to highΓÇôspeed internet and the power and speed of the new generation of computers, a researcher now faces somevery challenging phenomena and must deal with an everΓÇôincreasing amount of data. In order to find useful information and hidden patterns underlying the data, a researcher may use various dataΓÇômining methods and techniques for random samples. Adding a time dimension to these large databases certainly introduces new aspects and challenges.

Following on from his highly successful and much lauded book, Time Series AnalysisΓÇôUnivariate and Multivariate Methods, this new work focuses is on high dimensional multivariate time series, illustrated with many high dimensional empirical time series.

Multivariate Time Series Analysis and its Applications includes many topics that are not found in general multivariate time series books:
repeated measurements space time series modelling dimension reduction
This book is designed for an advanced time series analysis course, where researchΓÇôoriented projects will be suggested rather than introductory topics covered. It is a mustΓÇôhave for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.

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