Similarity Search of Time Series with Moving Average Based Indexing
نویسندگان
چکیده
منابع مشابه
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 کاملCensored 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 کاملTime-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 کاملSimilarity Search on Time Series Based on Threshold Queries
Similarity search in time series data is required in many application fields. The most prominent work has focused on similarity search considering either complete time series or similarity according to subsequences of time series. For many domains like financial analysis, medicine, environmental meteorology, or environmental observation, the detection of temporal dependencies between different ...
متن کاملIdentification 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 کاملذخیره 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 Software
سال: 2008
ISSN: 1000-9825
DOI: 10.3724/sp.j.1001.2008.02349