Asymptotic theory for stationary processes

By Wei Biao Wu. 2011

125 citations recorded by the source corpus.

Subfields: Applied Mathematics, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/245d51ccef08c51a2395e59b60da0e825f83358f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

In Economics and Econometrics

In Finance

Citations in the corpus

Probability and moment inequalities under dependence (2013, methodology): “Our Theorem 1 provides an upper bound for ∥S∗n∥p using the functional dependence measure θn,p which is easily computable in many applications; see Wu (2011).”
Performance bounds for parameter estimates of high-dimensional linear models with correlated errors (2016, background): “The framework (1.2) is general enough to include a wide range of stochastic processes ([38, 44]).”
Gaussian Approximation for High Dimensional Time Series (2015, background): “In the scalar case with p = 1, (3) allows a very general class of stationary processes (cf. Wiener (1958), Rosenblatt (1971), Priestley (1988), Tong (1990), Wu (2005), Tsay (2005), Wu (2011)).”
Covariance and precision matrix estimation for high-dimensional time series (2013, methodology): “In Wu (2011) functional dependence measures were computed for some commonly used linear and nonlinear stationary processes.”
Estimation and Selection of Spatial Weight Matrix in a Spatial Lag Model (2019, methodology): “The predictive dependence measure, introduced in Definition 2 of Wu (2011), quantifies the degree of dependence of outputs on inputs in physical systems, similar to our variables defined in (3.”
Komlós–Major–Tusnády approximation under dependence (2014, methodology): “and others and led to the theory of weak convergence of probability measures on metric spaces; see, for example, Billingsley (1968). In another direction, Strassen (1964) used the Skorohod representation theorem to get an almost sure approximation of partial sums of i.”