The partially monotone tensor spline estimation of joint distribution function with bivariate current status data
نویسندگان
چکیده
Approved: Thesis Supervisor Title and Department
منابع مشابه
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...
متن کاملData envelope fitting with constrained polynomial splines
Estimation of support frontiers and boundaries often involves monotone and/or concave edge data smoothing. This estimation problem arises in various unrelated contexts, such as optimal cost and production assessments in econometrics and master curve prediction in the reliability programs of nuclear reactors. Very few constrained estimators of the support boundary of a bivariate distribution hav...
متن کاملSieve Estimation with Bivariate Interval Censored Data
Bivariate interval censored data arises in many applications. However, both theoretical and computational investigations for this type of data are limited because of the complicated structure of bivariate censoring. In this paper, we propose a two-stage spline-based sieve estimator for the association between two event times with bivariate case 2 interval censored data. A smooth and explicit es...
متن کاملTwo-stage estimation using copula function
Maximum likelihood estimation of multivariate distributions needs solving a optimization problem with large dimentions (to the number of unknown parameters) but two- stage estimation divides this problem to several simple optimizations. It saves significant amount of computational time. Two methods are investigated for estimation consistency check. We revisit Sankaran and Nair's bivari...
متن کاملAlmost Sure Convergence of Kernel Bivariate Distribution Function Estimator under Negative Association
Let {Xn ,n=>1} be a strictly stationary sequence of negatively associated random variables, with common distribution function F. In this paper, we consider the estimation of the two-dimensional distribution function of (X1, Xk+1) for fixed $K /in N$ based on kernel type estimators. We introduce asymptotic normality and properties and moments. From these we derive the optimal bandwidth...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016