Abstract:
Let
X1,…,
Xnbe i.i.d. random with density function
f(
x), which has the shape of a steep head and a heave tail such as log-normal and Weibull density function. Consider a transformation
T:
Yi=
T(
Xi), where
Yi obey a density function
g(
y) which has a minimum error of estimate. The estimate
f(
x)can be obtained by
f(
x)=
T'(
x)
g(
T(
x)). In this paper we present a iterative algorithm of the transformed kernel estimate and discuss the performance of estimate. A Monte Carlo simulations show that the transformed kernel estimate is suitable for the estimate of log-normal and Weibull density function.