Spectral Analysis of Economic Time Series. (PSME-1)
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A01=Clive William John Granger
A01=Michio Hatanaka
Age Group_Uncategorized
Age Group_Uncategorized
Amplitude
Author_Clive William John Granger
Author_Michio Hatanaka
Autocorrelation
Autocovariance
automatic-update
Autoregressive model
Business cycle
Business Cycle Indicators
Business statistics
Calculation
Category1=Non-Fiction
Category=KCA
Category=KCH
Category=KCJ
Category=KCP
Chi-squared test
Commodity
COP=United States
Correlation coefficient
Covariance function
Covariance matrix
Cross-spectrum
Delivery_Delivery within 10-20 working days
Demodulation
Diagram (category theory)
Econometric model
Econometrics
Economic data
Economic indicator
Economic problem
Economic statistics
Economics
eq_business-finance-law
eq_isMigrated=2
eq_non-fiction
Estimation
Estimation theory
Forecast error
Fourier analysis
Fourier series
Frequency band
Gross national product
Industrial production index
Interest rate
Inventory control
Inventory investment
Kernel density estimation
Keynesian economics
Language_English
Logarithm
Logistic function
Mathematical economics
Measures of national income and output
Monte Carlo method
National Bureau of Economic Research
PA=Available
Periodic function
Phase diagram
Prediction
Price controls
Price index
Price level
Price_€20 to €50
Probability and statistics
Probability distribution
Probability theory
Proportionality (mathematics)
PS=Active
Quantity
Rates (tax)
Rounding
softlaunch
Spectral density
Spectral method
Stationary process
Statistical hypothesis testing
Stochastic process
Supply (economics)
Test statistic
Theoretical Value
Time series
Transfer function
Trend line (technical analysis)
Variable (mathematics)
Variance
Weighted arithmetic mean
Wholesale price index
Product details
- ISBN 9780691624785
- Weight: 425g
- Dimensions: 152 x 235mm
- Publication Date: 08 Dec 2015
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for time series data. New methods for analyzing series containing no trends have been developed by communication engineering, and much recent research has been devoted to adapting and extending these methods so that they will be suitable for use with economic series. This book presents the important results of this research and further advances the application of the recently developed Theory of Spectra to economics. In particular, Professor Hatanaka demonstrates the new technique in treating two problems-business cycle indicators, and the acceleration principle existing in department store data. Originally published in 1964. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions.
The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
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