Autoregressive moving average modeling for spectral parameter estimation from a multigradient echo chemical shift acquisition

نویسندگان
چکیده

برای دانلود رایگان 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

Nonlinear autoregressive and nonlinear autoregressive moving average model parameter estimation by minimizing hypersurface distance

The least squares (LS) can be used for nonlinear autoregressive (NAR) and nonlinear autoregressive moving average (NARMA) parameter estimation. However, for nonlinear cases, the LS results in biased parameter estimation due to its assumption that the independent variables are noise free. The total least squares (TLS) is another method that can used for nonlinear parameter estimation to increase...

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

Minimum Message Length Inference and Parameter Estimation of Autoregressive and Moving Average Models

This technical report presents a formulation of the parameter estimation and model selection problem for Autoregressive (AR) and Moving Average (MA) models in the Minimum Message Length (MML) framework. In particular, it examines suitable priors for both classes of models, and subsequently derives message length expressions based on the MML87 approximation. Empirical results demonstrate the new...

متن کامل

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

Dissertation Time - Frequency - Autoregressive - Moving - Average Modeling of Nonstationary Processes

This thesis introduces time-frequency-autoregressive-moving-average (TFARMA) models for underspread nonstationary stochastic processes (i.e., nonstationary processes with rapidly decaying TF correlations). TFARMAmodels are parsimonious as well as physically intuitive and meaningful because they are formulated in terms of time shifts (delays) and Doppler frequency shifts. They are a subclass of ...

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: Medical Physics

سال: 2009

ISSN: 0094-2405

DOI: 10.1118/1.3075819