Generalized gamma kernel density estimation for nonnegative data and its bias reduction
Generalized gamma kernel density estimation for nonnegative data and its bias reduction
复制标题
非负数据的广义伽玛核密度估计及其偏差减少
DOI：
10.1080/10485252.2018.1457791
复制
发表时间：
2018
影响因子：
1.2
通讯作者：
Kakizawa Yoshihide
中科院分区：
文献类型：
--
作者：
Igarashi Gaku;Kakizawa Yoshihide
我们考虑使用广义伽玛密度的非负数据的密度估计。这里强调的是，允许负指数。我们表明，对于每个正或负指数，（i）广义伽玛核密度估计，没有偏见减少，有平均积分平方误差（MISE）的顺序，在其他边界偏差自由密度估计从现有文献中，和（ii）偏见减少的版本有MISE的顺序，其中n是样本大小。我们通过仿真说明了所提出的估计器的有限样本性能。
We consider density estimation for nonnegative data using generalised gamma density. What is being emphasised here is that a negative exponent is allowed. We show that, for each positive or negative exponent,(i) generalised gamma kernel density estimator, without bias reduction, has the mean integrated squared error (MISE) of order, as in other boundary-bias-free density estimators from the existing literature, and that (ii) the bias-reduced versions have the MISEs of order, where n is the sample size. We illustrate the finite sample performance of the proposed estimators through the simulations.