Kernel density estimation for spatial processes: the L 1 theory

72 citations recorded by the source corpus.

How researchers see this paper

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

Asymptotic theory for nonparametric regression with spatial data (2011, background): “Notice that Xn i;j=1;i 6=j ij = Xni 1 ji=1 ni;i=1;2 Cov fv(0; 0); v(j1; j2)g : Tran (1990), Hallin, Lu, and Tran (2001, 2004b), for example, established consistency results for kernel density estimates with lattice spatial data, under di¤erent conditions from those in Theorem 3.”
Asymptotic theory for stationary processes (2011, background): “Theorem 3(ii) follows from Hannan (1979) and Dedecker and Merlevéde (2003).”
Estimation in semiparametric spatial regression (2006, methodology): “The L1 theory was established by Carbon, Hallin and Tran [4], and developed further by Hallin, Lu and Tran [ 15 ] under spatial stability conditions, including spatial linear and nonlinear processes, without imposing the less verifiable mixing conditions.”
Kernel regression estimation for continuous spatial processes (2007, background): “references: Tran [46], Tran and Yakowitz [47], Carbon, Hallin, and Tran [14], Carbon, Tran, and Wu [15], Hallin, Lu, and Tran [ 26 ], and Carbon [13].”