# Introduction to Statistical Time Series.

@inproceedings{Chatfield1976IntroductionTS, title={Introduction to Statistical Time Series.}, author={Chris Chatfield and Wayne A. Fuller}, year={1976} }

Moving Average and Autoregressive Processes. Introduction to Fourier Analysis. Spectral Theory and Filtering. Some Large Sample Theory. Estimation of the Mean and Autocorrelations. The Periodogram, Estimated Spectrum. Parameter Estimation. Regression, Trend, and Seasonality. Unit Root and Explosive Time Series. Bibliography. Index.

## 5,127 Citations

Repeated Time Series Analysis of

- Mathematics
- 1990

This article develops a theory and methodology for repeated time series (RTS) measurements on autoregressive integrated moving average-noise (ARIMAN) process. The theory enables us to relax the…

Repeated time series analysis of ARIMA-noise models

- Mathematics
- 1990

This article develops a theory and methodology for repeated time series (RTS) measurements on autoregressive integrated moving average-noise (ARIMAN) process. The theory enables us to relax the…

The Asymptotic Distribution of the Sample Autocorrelations for an Integrated ARMA Process

- Mathematics
- 1980

Abstract The behavior of the sample autocorrelation function, r(k), for an integrated autoregressive moving average time series is examined. The nonnormal asymptotic distribution of r(k) is…

Regression Models with Time Series Errors

- Mathematics
- 1984

Abstract The time series regression models in which the errors of regression equations follow stationary or nonstationary autoregressive moving average models are considered. Convergence properties…

Seasonality analysis of time series in partial linear models

- Mathematics
- 2009

Seasonality analysis is one of the classic topics in time series. This paper studies techniques for seasonality analysis when the trend function is unspecified. The asymptotic properties of the…

Efficient inference for autoregressive coefficients in the presence of trends

- MathematicsJ. Multivar. Anal.
- 2013

Consistency of the maximum likelihood estimators for nonstationary ARMA regressions with time trends

- Mathematics
- 2000

ON SMOOTHING TIME SERIES DATA USING A CLASSICAL MOVING AVERAGE FORMULA

- Mathematics
- 2002

In time series realizations, assuming that the trend component to be approximated by a polynomial in time, smoothing filters based on a moving-average formula are proposed which link the degree of…

On the Best Unbiased Estimate for the Mean of a Short Autoregressive Time Series

- MathematicsEconometric Theory
- 1992

A simple formula for computing the best linear unbiased estimate of the mean of an autoregressive process as well as its variance is given. Numerical results show that the estimate can have much…