1.

Record Nr.

UNICASVIA0079107

Autore

Merli, Giorgio

Titolo

I nuovi paradigmi del management : i processi gestionali come chiave di successo nell'era dell'e-business e dell'ipercompetizione / Giorgio Merli

Pubbl/distr/stampa

Milano, : Il sole-24 ore, 1999

ISBN

8871879848

Descrizione fisica

271 p. ; 23 cm

Collana

L'impresa

Disciplina

658.4001

Soggetti

Aziende - Direzione - Teoria

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

In appendice: Il modello EFQM per l'eccellenza, 1999, dello stesso A.



2.

Record Nr.

UNINA9911019862403321

Autore

Hannan E. J (Edward James), <1921->

Titolo

Multiple time series / / E. J. Hannan

Pubbl/distr/stampa

New York, : Wiley, 1970

ISBN

9786612307607

9781282307605

1282307606

9780470316429

047031642X

9780470317136

0470317132

Descrizione fisica

1 online resource (552 p.)

Collana

Wiley series in probability and mathematical statistics

Disciplina

519.232

519.8

Soggetti

Mathematical statistics

Time-series analysis

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliography: p. 519-527.

Nota di contenuto

Multiple Time Series; Contents; PART I. BASIC THEORY; CHAPTER I. INTRODUCTORY THEORY; 1. Introduction; 2. Differentiation and Integration of Stochastic Processes; 3. Some Special Models; 4. Stationary Processes and their Covariance Structure; 5. Higher Moments; 6. Generalized Random Processes; EXERCISES; APPENDIX; CHAPTER II. THE SPECTRAL THEORY OF VECTOR PROCESSES; 1. Introduction; 2. The Spectral Theorems for Continuous-Time Stationary Processes; 3. Sampling a Continuous-Time Process. Discrete Time Processes; 4. Linear Filters; 5 . Some Special Models

6. Some Spectral Theory for Nonstationary Processes7. Nonlinear Transformations of Random Processes; 8. Higher Order Spectra; 9. Spectral Theory for GRP; 10. Spectral Theories for Homogeneous Random Processes on Other Spaces; 11. Filters, General Theory; EXERCISES; APPENDIX; CHAPTER III. PREDICTION THEORY AND SMOOTHING; 1. Introduction; 2. Vector Discrete-Time Prediction for



Rational Spectra; 3. The General Theory for Stationary, Discrete-Time, Scalar Processes; 4. The General Theory for Stationary, Continuous-Time, Scalar Processes; 5. Vector Discrete-Time Prediction

6. Problems of Interpolation7. Smoothing and Signal Measurement; 8. Kalman Filtering; 9. Smoothing Filters; EXERCISES; PART II. INFERENCE; CHAPTER IV. THE LAWS OF LARGE NUMBERS AND THE CENTRAL LIMIT THEOREM; 1. Introduction; 2. Strictly Stationary Processes. Ergodic Theory; 3. Second-Order Stationary Processes. Ergodic Theory; 4. The Central Limit Theorem; EXERCISES; APPENDIX; CHAPTER V. INFERENCE ABOUT SPECTRA; 1. Introduction; 2. The Finite Fourier Transform; 3. Alternative Computational Procedures for the FFT; 4. Estimates of Spectral for large Nand N/M

5. The Asymptotic Distribution of Spectral Estimates6. Complex Multivariate Analysis; EXERCISES; APPENDIX; CHAPTER VI. INFERENCE FOR RATIONAL SPECTRA; 1. Introduction; 2. Inference for Autoregressive Models. Asymptotic Theory; 3. Inference for Autoregressive Models. Some Exact Theory; 4. Moving Average and Mixed Autoregressive, Moving Average Models. Introduction; 5. The Estimation of Moving Average and Mixed Moving Average Autoregressive Models Using Spectral Methods; 6. General Theories of Estimation for Finite Parameter Models; 7. Tests of Goodness of Fit

8. Continuous-Time Processes and Discrete ApproximationsEXERCISES; APPENDIX; CHAPTER VII. REGRESSION METHODS; 1. Introduction; 2. The Efficiency of Least Squares. Fixed Sample Size; 3. The Efficiency of Least Squares. Asymptotic Theory; 4. The Efficient Estimation of Regressions; 5. The Effects of Regression Procedures on Analysis of Residuals; 6. Tests for Periodicities; 7. Distributed Lag Relationships; EXERCISES; APPENDIX; MATHEMATICAL APPENDIX; BIBLIOGRAPHY; TABLE OF NOTATIONS; INDEX

Sommario/riassunto

The Wiley Series in Probability and Statistics is a collection of topics of current research interests in both pure and applied statistics and probability developments in the field and classical methods. This series provides essential and invaluable reading for all statisticians, whether in academia, industry, government, or research.