Parameter Estimation of Autoregressive Integrated Processes by Least Squares

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

Decomposition Methods for Least Squares Parameter Estimation

In this paper least squares method with matrix decomposition is revisited and a multiple model formulation is proposed The proposed formulation takes advantage of the well established decomposition methods but possesses a multiple model structure which leads to simpler and more exible implementations and produces more infor mation than the original least squares methods Several application exam...

متن کامل

Parameter estimation for non-Gaussian autoregressive processes

It is proposed to jointly estimate the parameters of nonGaussian autoregressive (AR) processes in a Bayesian context using the Gibbs sampler. Using the Markov chains produced by the sampler an approximation to the vector MAP estimator is implemented. The results reported here used AR(4) models driven by noise sequences where each sample is iid as a two component Gaussian sum mixture. The result...

متن کامل

Least squares estimation in a simple random coefficient autoregressive model.∗

The question we discuss is whether a simple random coefficient autoregressive model with infinite variance can create the long swings, or persistence, which are observed in many macro economic variables. The model is defined by yt = stρyt−1 + εt, t = 1, . . . , n, where st is an i.i.d. binary variable with p = P (st = 1), independent of εt i.i.d. with mean zero and finite variance. We say that ...

متن کامل

Weighted Least Squares Approximate Restricted Likelihood Estimation for Vector Autoregressive Processes

We derive a weighted least squares approximate restricted likelihood estimator for a kdimensional pth order autoregressive model with intercept, for which exact likelihood optimization is generally infeasible due to the parameter space which is complicated and highdimensional, involving pk2 parameters. The weighted least squares estimator has significantly reduced bias and mean squared error th...

متن کامل

Sequential Parameter Estimation of Time-Varying Non-Gaussian Autoregressive Processes

Parameter estimation of time-varying non-Gaussian autoregressive processes can be a highly nonlinear problem. The problem gets even more difficult if the functional form of the time variation of the process parameters is unknown. In this paper, we address parameter estimation of such processes by particle filtering, where posterior densities are approximated by sets of samples (particles) and p...

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: The Annals of Statistics

سال: 1980

ISSN: 0090-5364

DOI: 10.1214/aos/1176344962