Approximation of a random process with variable smoothness
Enkelejd Hashorva, Mikhail Lifshits, Oleg Seleznjev
Abstract
Open-access reader
Enkelejd Hashorva, Mikhail Lifshits, Oleg Seleznjev
Abstract
Open-access reader
We consider the rate of piecewise constant approximation to a locally stationary process $X(t),t\in [0,1]$, having a variable smoothness index $α(t)$. Assuming that $α(\cdot)$ attains its unique minimum at zero and satisfies the regularity condition, we propose a method for construction of observation points (composite dilated design) and find an asymptotics for the integrated mean square error, where a piecewise constant approximation $X_n$ is based on $N(n)\sim n$ observations of $X$. Further, we prove that the suggested approximation rate is optimal, and then show how to find an optimal constant.
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We consider the rate of piecewise constant approximation to a locally stationary process $X(t),t\in [0,1]$, having a variable smoothness index $α(t)$. Assuming that $α(\cdot)$ attains its unique minimum at zero and satisfies the regularity condition, we propose a method for construction of observation points (composite dilated design) and find an asymptotics for the integrated mean square error, where a piecewise constant approximation $X_n$ is based on $N(n)\sim n$ observations of $X$. Further, we prove that the suggested approximation rate is optimal, and then show how to find an optimal constant.
Key concepts: Smoothness, Piecewise, Constant (computer programming), Mathematics, Zero (linguistics), Square (algebra), Variable (mathematics), Random variable