Sabtu, 27 Desember 2014

Forecasting with Certain ARIMA Models



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Below are some topics which important for your thesis/dissertation:
FORECASTING
Minimum Mean Square Error Forecasting
Deterministic Trends
ARIMA Forecasting
Prediction Limits
Forecasting Illustrations
Updating ARIMA Forecasts
Forecast Weights and Exponentially Weighted
Moving Averages
Forecasting Transformed Series
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Forecasting with Certain ARIMA Models
Conditional Expectation
FMinimum Mean Square Error Prediction
GThe Truncated Linear Process
HState Space Models
SEASONAL MODELS
Seasonal ARIMA Models
Multiplicative Seasonal ARMA Models
Nonstationary Seasonal ARIMA Models
Model Specification, Fitting, and Checking
Forecasting Seasonal Models
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TIME SERIES REGRESSION MODELS
Intervention Analysis
Outliers
Spurious Correlation
Prewhitening and Stochastic Regression
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TIME SERIES MODELS OF HETEROSCEDASTICITY
Some Common Features of Financial Time Series
The ARCH Model
GARCH Models
Maximum Likelihood Estimation
Model Diagnostics
Conditions for the Nonnegativity of the Conditional Variances
Some Extensions of the GARCH Model
Another ExampleThe Daily USD/HKD Exchange Rates
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Formulas for the Generalized Portmanteau Tests to spectral analysis
The Periodogram
The Spectral Representation and Spectral Distribution.
The Spectral Density
Spectral Densities for ARMA Processes
Sampling Properties of the Sample Spectral Density
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Orthogonality of Cosine and Sine Sequences
ESTIMATING THE SPECTRUM
Smoothing the Spectral Density
Bias and Variance
Bandwidth
Confidence Intervals for the Spectrum
Leakage and Tapering
Autoregressive Spectrum Estimation
with Simulated Data
with Actual Data
Other Methods of Spectral Estimation

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