Selected Papers of Hirotugu Akaike: Springer Series in Statistics
Editat de Emanuel Parzen, Kunio Tanabe, Genshiro Kitagawaen Limba Engleză Paperback – 23 oct 2012
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Specificații
ISBN-13: 9781461272489
ISBN-10: 1461272483
Pagini: 448
Ilustrații: VIII, 434 p.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.62 kg
Ediția:Softcover reprint of the original 1st ed. 1998
Editura: Springer
Colecția Springer
Seriile Springer Series in Statistics, Perspectives in Statistics
Locul publicării:New York, NY, United States
ISBN-10: 1461272483
Pagini: 448
Ilustrații: VIII, 434 p.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.62 kg
Ediția:Softcover reprint of the original 1st ed. 1998
Editura: Springer
Colecția Springer
Seriile Springer Series in Statistics, Perspectives in Statistics
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
Foreword.- A Conversation with Hirotugu Akaike.- List of Publications of Hirotugu Akaike.- Papers.- 1. Precursors.- 1. On a zero-one process and some of its applications.- 2. On a successive transformation of probability distribution and its application to the analysis of the optimum gradient method.- 2. Frequency Domain Time Series Analysis.- 1. Effect of timing-error on the power spectrum of sampled-data.- 2. On a limiting process which asymptotically produces f-2 spectral density.- 3. On the statistical estimation of frequency response function.- 3. Time Domain Time Series Analysis.- 1. On the use of a linear model for the identification of feedback systems.- 2. Fitting autoregressive models for prediction.- 3. Statistical predictor identification.- 4. Autoregressive model fitting for control.- 5. Statistical approach to computer control of cement rotary kilns.- 6. Statistical identification for optimal control of supercritical thermal power plants.- 4. AIC and Parametrization.- 1. Information theory and an extension of the maximum likelihood princilple.- 2. A new look at the statistical model identification.- 3. Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes.- 4. Covariance matrix computation of the state variable of a stationary Gaussian process.- 5. Analysis of cross classified data by AIC.- 6. On linear intensity models for mixed doubly stochastic Poisson and self-exciting point processes.- 5. Bayesian Approach.- 1. A Baysian analysis of the minimum AIC procedure.- 2. A new look at the Bayes procedure.- 3. On the likelihood of a time series model.- 4. Likelihood and the Bayes procedure.- 5. Seasonal adjustment by a Bayesian modeling.- 6. A quasi Bayesian approach to outlier detection.- 7. On the fallacy of the likelihood principle.- 8. A Bayesian apporach to the analysis of earth tides.- 9. Factor analysis and AIC.- 6. General Views on Statistics.- 1. Prediction and entropy.- 2. Experiences on the development of time series models.- 3. Implications of informational point of view on the development of statistical science.