Adaptive estimation of the conditional cumulative distribution function from current status data

Efficient Estimation of the Density and Cumulative Distribution Function of the Generalized Rayleigh Distribution

The uniformly minimum variance unbiased (UMVU), maximum likelihood, percentile (PC), least squares (LS) and weighted least squares (WLS) estimators of the probability density function (pdf) and cumulative distribution function are derived for the generalized Rayleigh distribution. This model can be used quite effectively in modelling strength data and also modeling general lifetime data. It has...

Kernel estimation of multivariate cumulative distribution function

A smooth kernel estimator is proposed for multivariate cumulative distribution functions (cdf), extending the work of Yamato [H. Yamato, Uniform convergence of an estimator of a distribution function, Bull. Math. Statist. 15 (1973), pp. 69–78.] on univariate distribution function estimation. Under assumptions of strict stationarity and geometrically strong mixing, we establish that the proposed...

The partially monotone tensor spline estimation of joint distribution function with bivariate current status data

Approved: Thesis Supervisor Title and Department

Partially Monotone Tensor Spline Estimation of the Joint Distribution Function with Bivariate Current Status Data

The analysis of the joint distribution function with bivariate event time data is a challenging problem both theoretically and numerically. This paper develops a tensor spline-based sieve maximum likelihood estimation method to estimate the joint distribution function with bivariate current status data. The I-spline basis functions are used in approximating the joint distribution function in or...

Adaptive pointwise estimation of conditional density function