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Distribution-free strong consistency for nonparametric kernel regression involving nonlinear time series

✍ Scribed by Zudi Lu; Ping Cheng


Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
790 KB
Volume
65
Category
Article
ISSN
0378-3758

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✦ Synopsis


Under quite mild conditions on the kernel and on the bandwidth, the distribution-free strong consistency is proved for the kernel regression and the modified kernel regression of an ~-mi×in~ stationary sequence in time series context. The condition imposed on the mixing coefficients ..... . l,, ~=~ j. 1 is ~-~/::1.1 I (j)l <:xD (a>l, v>l) or z_,/I :~(J) <~c (a>l), which is simple and weaker than those in the literature.