Gaussian process approximations for multicolor Pólya urn models

Motivated by mathematical tissue growth modelling, we consider the problem of approximating the dynamics of multicolor Pólya urn processes that start with large numbers of balls of different colors and run for a long time. Using strong approximation theorems for empirical and quantile processes, we establish Gaussian process approximations for the Pólya urn processes. The approximating processes are sums of a multivariate Brownian motion process and an independent linear drift with a random Gaussian coefficient. The dominating term between the two depends on the ratio of the number of time steps n to the initial number of balls N in the urn. We also establish an upper bound of the form $c(n^{-1/2}+N^{-1/2})$ for the maximum deviation over the class of convex Borel sets of the step-n urn composition distribution from the approximating normal law.

Some asymptotic properties between smooth empirical and quantile processes for dependent random variables

Пусть $\widehat F_n$ - гладкая эмпирическая оценка, полученная интегрированием оценки плотности ядерного типа, построенной по случайной выборке размера $n$ из распределения с непрерывной функцией распределения $F$. В статье изучается отклонение почти наверное между гладким эмпирическим и гладким квантильным процессами при условии $\phi$-перемешивания и при условии сильного перемешивания. Для гладких квантилей в случае $\phi$-перемешивания и в случае сильного перемешивания выводится представление Бахадура-Кифера, как поточечное, так и равномерное. Эти результаты являются распространением результатов Бабу-Сингха (1978) и Ралеску (1992).

Weak approximations for empirical Lorenz curves and their Goldie inverses of stationary observations

By using Chibisov-O'Reilly type theorems for uniform empirical and quantile processes based on stationary observations, we establish a weak approximation theory for empirical Lorenz curves and their inverses used in economics. In particular, we obtain weak approximations for empirical Lorenz curves and their inverses also under the assumptions of mixing dependence, often used structures of dependence for observations.

Weak approximations for empirical Lorenz curves and their Goldie inverses of stationary observations

By using Chibisov-O'Reilly type theorems for uniform empirical and quantile processes based on stationary observations, we establish a weak approximation theory for empirical Lorenz curves and their inverses used in economics. In particular, we obtain weak approximations for empirical Lorenz curves and their inverses also under the assumptions of mixing dependence, often used structures of dependence for observations.