Records for the moving average of a time series

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

Time-Varying Moving Average Model for Autocovariance Nonstationary Time Series

In time series analysis, fitting the Moving Average (MA) model is more complicated than Autoregressive (AR) models because the error terms are not observable. This means that iterative nonlinear fitting procedures need to be used in place of linear least squares. In this paper, Time-Varying Moving Average (TVMA) models are proposed for an autocovariance nonstationary time series. Through statis...

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

Identification of Autoregressive Moving-Average Parameters of Time Series

,4bstme—A pmeedurefor sequentiaffy eatirnating the parameters and orders of mixed autoregmsive moving-average signaf modefs from tirneserfes data is presented. Iderrtfffftion ia performed by first fderstffying a purely asrtoregmwive aignaf model. Tire parametem and orders of tbe mixed autoregmsaive moving-average proeeaa are then gfven from tbe solutton of sfmple sdgebraic equations involving t...

متن کامل

Censored Time Series Analysis with Autoregressive Moving Average Models

Time series measurements are often observed with data irregularities, such as censoring due to a detection limit. Practitioners commonly disregard censored data cases which often result into biased estimates. We present an attractive remedy for handling autocorrelated censored data based on a class of autoregressive and moving average (ARMA) models. In particular, we introduce an imputation met...

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

ژورنال

عنوان ژورنال: Journal of Statistical Mechanics: Theory and Experiment

سال: 2020

ISSN: 1742-5468

DOI: 10.1088/1742-5468/ab5d08