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"'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text integrates the two strands into a coherent treatment, drawing together theory, data, computation and recent research. The theoretical framework includes formal definitions, theorems and proofs, which clearly set out the guaranteed 'safe operating zone' for the methods and allow users to assess whether data is in or near the zone. Extensive examples showcase the strengths and limitations of different methods in a range of cases: small classical data; data from medicine, biology, marketing and finance; high-dimensional data from bioinformatics; functional data from proteomics; and simulated data. High-dimension, low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code and problem sets complete the package. The text is suitable for graduate students in statistics and researchers in data-rich disciplines"--
Stabilt pris
5 kr dyrare
Sällan rea
Författare
Inge Koch
Serie
Del 32 i Cambridge series in statistical and probabilistic mathematics
Förlag
Cambridge University Press
Utgivningsår
2014
Sidantal
504
Språk
Engelska
Fysiska detaljer
ill., tab.
Dewey
519.5/35
ISBN
9780521887939
Inga erbjudanden tillgängliga just nu.
"'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text integrates the two strands into a coherent treatment, drawing together theory, data, computation and recent research. The theoretical framework includes formal definitions, theorems and proofs, which clearly set out the guaranteed 'safe operating zone' for the methods and allow users to assess whether data is in or near the zone. Extensive examples showcase the strengths and limitations of different methods in a range of cases: small classical data; data from medicine, biology, marketing and finance; high-dimensional data from bioinformatics; functional data from proteomics; and simulated data. High-dimension, low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code and problem sets complete the package. The text is suitable for graduate students in statistics and researchers in data-rich disciplines"--
Stabilt pris
5 kr dyrare
Sällan rea
Författare
Inge Koch
Serie
Del 32 i Cambridge series in statistical and probabilistic mathematics
Förlag
Cambridge University Press
Utgivningsår
2014
Sidantal
504
Språk
Engelska
Fysiska detaljer
ill., tab.
Dewey
519.5/35
ISBN
9780521887939
ISBN 9780521887939 jämförs hos alla butiker
"'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text integrates the two strands into a coherent treatment, drawing together theory, data, computation and recent research. The theoretical framework includes formal definitions, theorems and proofs, which clearly set out the guaranteed 'safe operating zone' for the methods and allow users to assess whether data is in or near the zone. Extensive examples showcase the strengths and limitations of different methods in a range of cases: small classical data; data from medicine, biology, marketing and finance; high-dimensional data from bioinformatics; functional data from proteomics; and simulated data. High-dimension, low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code and problem sets complete the package. The text is suitable for graduate students in statistics and researchers in data-rich disciplines"--
Stabilt pris
5 kr dyrare
Sällan rea
Författare
Inge Koch
Serie
Del 32 i Cambridge series in statistical and probabilistic mathematics
Förlag
Cambridge University Press
Utgivningsår
2014
Sidantal
504
Språk
Engelska
ISBN
9780521887939
