排序方式: 共有3条查询结果,搜索用时 15 毫秒
1
1.
生长曲线模型是一个典型的多元线性模型,
在现代统计学上占有重要地位. 文章首先基于Potthoff-Roy变换后的生长曲线模型,
采用自适应LASSO为惩罚函数给出了参数矩阵的惩罚最小二乘估计,
实现了变量的选择. 其次, 基于局部渐近二次估计,
对生长曲线模型的惩罚最小二乘估计给出了统一的近似估计表达式. 接着,
讨论了经过Potthoff-Roy变换后模型的惩罚最小二乘估计,
证明了自适应LASSO具有Oracle性质. 最后对几种变量选择方法进行了数据模拟.
结果表明自适应LASSO效果比较好. 另外, 综合考虑,
Potthoff-Roy变换优于拉直变换. 相似文献
2.
In the research it is frequently assumed
that the growth curve is a polynomial in time. In practice,
researchers mainly use higher-order polynomials to obtain more
precise estimates. But this method has many defects, such as the
model can be easily affected by outliers and the polynomial
hypothesis may be much strong in practice. So in this paper we first
proposed nonparametric approach, local polynomial, instead of
parametric method for estimation in growth curve model. We give the
nonparametric growth curve model, and its nonparametric estimation.
Then discuss the large sample character of local polynomial
estimate. The ideal theoretical choice of a local bandwidth is also
discussed in detail in this paper. Finally, through the simulation
study, from the fitting curve and average square error box plot we
can clearly see that the performance of nonparametric approach is
much better than parametric technique. 相似文献
3.
1