Moving - Average Representation of Autoregressive Approximations

نویسنده

  • Peter B Uhlmann
چکیده

We study the properties of an MA1-representation of an autoregressive a p p r o x-imation for a stationary, real-valued process. In doing so we g i v e an extension of Wiener's Theorem in the deterministic approximation setup. When dealing with data, we can use this new key result to obtain insight i n to the structure of MA1-representations of tted autoregressive models where the order increases with the sample size. In particular, we show strong consistency of the MA1-transfer function via autoregressive approximation.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Modified Maximum Likelihood Estimation in First-Order Autoregressive Moving Average Models with some Non-Normal Residuals

When modeling time series data using autoregressive-moving average processes, it is a common practice to presume that the residuals are normally distributed. However, sometimes we encounter non-normal residuals and asymmetry of data marginal distribution. Despite widespread use of pure autoregressive processes for modeling non-normal time series, the autoregressive-moving average models have le...

متن کامل

Structure of Wavelet Covariance Matrices and Bayesian Wavelet Estimation of Autoregressive Moving Average Model with Long Memory Parameter’s

In the process of exploring and recognizing of statistical communities, the analysis of data obtained from these communities is considered essential. One of appropriate methods for data analysis is the structural study of the function fitting by these data. Wavelet transformation is one of the most powerful tool in analysis of these functions and structure of wavelet coefficients are very impor...

متن کامل

Rank-Based Estimation for Autoregressive Moving Average Time Series Models

We establish asymptotic normality and consistency for rank-based estimators of autoregressive-moving average model parameters. The estimators are obtained by minimizing a rank-based residual dispersion function similar to the one given in L.A. Jaeckel [Estimating regression coefficients by minimizing the dispersion of the residuals, Ann. Math. Statist. 43 (1972) 1449–1458]. These estimators can...

متن کامل

Statistical trend analysis and forecast modeling of air pollutants

The study provides a statistical trend analysis of different air pollutants using Mann-Kendall and Sen’s slope estimator approach on past pollutants statistics from air quality index station of Varanasi, India. Further, using autoregressive integrated moving average model, future values of air pollutant levels are predicted. Carbon monoxide, nitrogen dioxide, sulphur dioxide, particu...

متن کامل

Bayesian Analysis of Order Uncertainty in ARIMA Models

In this paper we extend the work of Brooks and Ehlers (2002) and Brooks et al. (2003) by constructing efficient proposal schemes for reversible jump MCMC in the context of autoregressive moving average models. In particular, the full conditional distribution is not available for the added parameters and approximations to it are provided by suggesting an adaptive updating scheme which automatica...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1995