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Limit Theorems for Kernel-type Estimators for the Time of Change by Irina Grabovsky; Lajos Horváth; Marie Hušková is a Mathematics article available to read on EtoBox.

What is Limit Theorems for Kernel-type Estimators for the Time of Change about?

We use kernel-type estimators to estimate the time of change in the mean in a sequence of independent observations. Assuming that the size of the change is small two types of limit distributions are derived. The forms of the limit distributions depend on the behavior of the kernel at the end points. The argmax of a two-sided Brownian motion with polynomial drift is a possible limit, while the normal distribution is the limit when the kernel is zero at both boundaries.

Who reads Limit Theorems for Kernel-type Estimators for the Time of Change?

Author

Irina Grabovsky; Lajos Horváth; Marie Hušková

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0378-3758)

Published

2000

Language

EN

Field

Mathematics (Physical Sciences)