Logspline Density Estimation for Censored Data
针对右删失、左删失或区间删失数据，提出对数样条密度估计方法，通过牛顿-拉夫森法和最速上升搜索求解最大似然方程，并用AIC或BIC自动选择最终模型。
Logspline density estimation is developed for data that may be right censored, left censored or interval censored.In solving the maximum likelihood equations, the Newton-Raphson method is augmented by occasional searches in the direction of steepest ascent.A fully automatic method, which may involve stepwise knot deletion and either AIC or BIC, is used to select the fin~l model.Also, a user interface based on S is described for obtaining estimates of the density function, distribution function and quantile function and for generating a random sample from the fitted distribution.