Time Series Analysis: Regression TechniquesSAGE, 1990 - Всего страниц: 95 "The text gives a good basis for understanding the ideas of the time series models and estimation, without overwhelming readers with the complexity of the subject." --Journal of the American Statistical Association Completely revised and updated, this second edition of Time Series Analysis examines techniques for the study of change based on regression analysis. Ostrom demonstrates how these regression techniques may be employed for hypothesis testing, estimating, and forecasting. In addition, analysis strategies for both lagged and nonlagged models are presented and alternative time-dependent processes are explored. |
Содержание
Series Editors Introduction | 8 |
Conventional Tests for Autocorrelation | 27 |
Small Sample Properties | 35 |
Extension to Multiple Regression | 41 |
Testing for HigherOrder Processes | 48 |
Ratio Goal Model Reconsidered | 56 |
Forecasting | 76 |
Forecasting U S Defense Expenditures | 86 |
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Другие издания - Просмотреть все
Time Series Analysis: Regression Techniques, Том 9;Том 1990 Charles W. Ostrom Просмотр фрагмента - 1990 |
Часто встречающиеся слова и выражения
ACF and PACF Applying OLS approach AREG assume autocorrelation function Beach-McKinnon bias Box-Jenkins coefficient correlograms d₁ dependent variable discussed distributed lag disturbance term e₁ EGLS estimates EGLS residuals equation 2.1 error process error term esti estimated residuals evaluation ex-ante-forecasts ex-post-forecasts example exogenous expected value Figure first-order autoregressive process following command forecast error Hildreth-Lu instrumental variables Johnston Kmenta lagged endogenous variables lagged values Malinvaud McCleary and Hay monograph moving average process naive model nonautoregression assumption Note null hypothesis numbers in parentheses observations obtain OLS estimates Ostrom P₁ parameters positive serial correlation possible postsample Prais-Winsten present problem procedure random random variable ratio goal model revised ratio goal sample serial correlation series regression analysis series regression model SPSS statistic t-ratios technique timated time-dependent process tion transformation U.S. defense expenditure U.S. defense spending U.S. spending USSR USSR spending V₁ Wonnacott and Wonnacott Y₁
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