Dimension Free and Infinite Variance Tail Estimates on Poisson Space
نویسندگان
چکیده
منابع مشابه
Dimension free and infinite variance tail estimates on Poisson space
Concentration inequalities are obtained on Poisson space, for random functionals with finite or infinite variance. In particular, dimension free tail estimates and exponential integrability results are given for the Euclidean norm of vectors of independent functionals. In the finite variance case these results are applied to infinitely divisible random variables such as quadratic Wiener functio...
متن کاملBootstrapping 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 کاملDimitri Shlyakhtenko Lower Estimates on Microstates Free Entropy Dimension
By proving that certain free stochastic differential equations with analytic coefficients have stationary solutions, we give a lower estimate on the microstates free entropy dimension of certain n-tuples 1. In particular, for small q, q-deformed free group factors have no Cartan subalgebras. An essential tool in our analysis is a free analog of an inequality between Wasserstein distance and Fis...
متن کاملRevised estimates of dimension and exercise variance components in assessment center postexercise dimension ratings.
The authors reanalyzed assessment center (AC) multitrait-multimethod (MTMM) matrices containing correlations among postexercise dimension ratings (PEDRs) reported by F. Lievens and J. M. Conway (2001). Unlike F. Lievens and J. M. Conway, who used a correlated dimension-correlated uniqueness model, we used a different set of confirmatory-factor-analysis-based models (1-dimension-correlated Exerc...
متن کاملMoving 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 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: Acta Applicandae Mathematicae
سال: 2007
ISSN: 0167-8019,1572-9036
DOI: 10.1007/s10440-007-9084-3