Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Khmaladze, Estate V."'
Autor:
Algeri, Sara, Khmaladze, Estate V.
Thousands of experiments are analyzed and papers are published each year involving the statistical analysis of grouped data. While this area of statistics is often perceived - somewhat naively - as saturated, several misconceptions still affect every
Externí odkaz:
http://arxiv.org/abs/2406.09195
Autor:
Khmaladze, Estate V.
Recently a distribution free approach for testing parametric hypotheses based on unitary transformations has been suggested in \cite{Khm13, Khm16, Khm17} and further studied in \cite{Ngu17} and \cite{Rob19}. In this note we show that the transformati
Externí odkaz:
http://arxiv.org/abs/2002.02594
In the classical two-sample problem, the conventional approach for testing distributions equality is based on the difference between the two marginal empirical distribution functions, whereas a test for independence is based on the contrast between t
Externí odkaz:
http://arxiv.org/abs/1806.05137
Autor:
Khmaladze, Estate V.
Publikováno v:
In Journal of Statistical Planning and Inference December 2021 215:72-84
Publikováno v:
Annals of Statistics 2015, Vol. 43, No. 2, 878-902
Let $(X_1,Y_1),\ldots,(X_n,Y_n)$ be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima $\bigv
Externí odkaz:
http://arxiv.org/abs/1504.00465
Autor:
Khmaladze, Estate V., Weil, Wolfgang
In recent work by Khmaladze and Weil (2008) and by Einmahl and Khmaladze (2011), limit theorems were established for local empirical processes near the boundary of compact convex sets $K$ in $\R$. The limit processes were shown to live on the normal
Externí odkaz:
http://arxiv.org/abs/1309.4945
Publikováno v:
Bernoulli 2011, Vol. 17, No. 2, 545-561
We define the local empirical process, based on $n$ i.i.d. random vectors in dimension $d$, in the neighborhood of the boundary of a fixed set. Under natural conditions on the shrinking neighborhood, we show that, for these local empirical processes,
Externí odkaz:
http://arxiv.org/abs/1104.4220
Autor:
Khmaladze, Estate V., Koul, Hira L.
Publikováno v:
Annals of Statistics 2009, Vol. 37, No. 6A, 3165-3185
This paper discusses asymptotically distribution free tests for the classical goodness-of-fit hypothesis of an error distribution in nonparametric regression models. These tests are based on the same martingale transform of the residual empirical pro
Externí odkaz:
http://arxiv.org/abs/0909.0170
Autor:
Khmaladze, Estate V., Koul, Hira L.
Publikováno v:
Annals of Statistics 2004, Vol. 32, No. 3, 995-1034
This paper discusses two goodness-of-fit testing problems. The first problem pertains to fitting an error distribution to an assumed nonlinear parametric regression model, while the second pertains to fitting a parametric regression model when the er
Externí odkaz:
http://arxiv.org/abs/math/0406518