M-estimation for autoregressions with infinite variance

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

Moving Average Processes with Infinite Variance

The sample autocorrelation function (acf) of a stationary process has played a central statistical role in traditional time series analysis, where the assumption is made that the marginal distribution has a second moment. Now, the classical methods based on acf are not applicable in heavy tailed modeling. Using the codifference function as dependence measure for such processes be shown it be as...

متن کامل

Nonparametric density estimation for linear processes with infinite variance

We consider nonparametric estimation of marginal density functions of linear processes by using kernel density estimators. We assume that the innovation processes are i.i.d. and have infinite-variance. We present the asymptotic distributions of the kernel density estimators with the order of bandwidths fixed as h = cn−1/5, where n is the sample size. The asymptotic distributions depend on both ...

متن کامل

Bootstrapping M-estimates in Regression and Autoregression with Infinite Variance

The limiting distribution for M -estimates in a regression or autoregression model with heavy-tailed noise is generally intractable, which precludes its use for inference purposes. Alternatively, the bootstrap can be used to approximate the sampling distribution of the M -estimate. In this paper, we show that the bootstrap procedure is asymptotically valid for a class of M -estimates provided t...

متن کامل

M-Estimation of Wavelet Variance

The wavelet variance provides a scale-based decomposition of the process variance for a time series or random field. It has seen increasing use in geophysics, astronomy, genetics, hydrology, medical imaging, oceanography, soil science, signal processing and texture analysis. In practice, however, data collected in the form of a time series or random field often suffer from various types of cont...

متن کامل

Estimation of AR Parameters in the Presence of Additive Contamination in the Infinite Variance Case

If we try to estimate the parameters of the AR process {Xn} using the observed process {Xn+Zn} then these estimates will be badly biased and not consistent but we can minimize the damage using a robust estimation procedure such as GM-estimation. The question is does additive contamination affect estimates of “core” parameters in the infinite variance case to the same extent that it does in the ...

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: Stochastic Processes and their Applications

سال: 1992

ISSN: 0304-4149

DOI: 10.1016/0304-4149(92)90142-d