✦ LIBER ✦

Estimating a distribution function with truncated data

✍ Scribed by Shuyuan He

Publisher: Institute of Applied Mathematics, Chinese Academy of Sciences and Chinese Mathematical Society
Year: 1994
Tongue: English
Weight: 763 KB
Volume: 10
Category: Article
ISSN: 0168-9673
DOI: 10.1007/bf02006256

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Nonparametric Bayes estimation of a dist

Nonparametric Bayes estimation of a distribution function with truncated data

✍ Mauro Gasparini 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 411 KB

A truncation bias affects the observation of a pair of variables (X, Y), so that data are available only if Y ~<X. In such a situation, the nonparametric maximum likelihood estimator (NPMLE) of the distribution function of Y may have unpleasant features (Woodroofe, Ann. Statisr 13 (1985) 163-177). A

Nonparametric Estimation of the Bivariat

Nonparametric Estimation of the Bivariate Survival Function with Truncated Data

✍ Mark J. van der Laan 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 766 KB

Randomly left or right truncated observations occur when one is concerned with estimation of the distribution of time between two events and when one only observes the time if one of the two events falls in a fixed time-window, so that longer survivial times have higher probability to be part of the

Asymptotic Properties of a Nonparametric

Asymptotic Properties of a Nonparametric Regression Function Estimator with Randomly Truncated Data

✍ Elias Ould-Saïd; Mohamed Lemdani 📂 Article 📅 2006 🏛 Springer Japan 🌐 English ⚖ 260 KB

Estimating a Distribution Function for C

Estimating a Distribution Function for Censored Time Series Data

✍ Zongwu Cai 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 159 KB

Consider a long term study, where a series of dependent and possibly censored failure times is observed. Suppose that the failure times have a common marginal distribution function, but they exhibit a mode of time series structure such as :-mixing. The inference on the marginal distribution function

Estimating the parameters of a truncated

Estimating the parameters of a truncated normal distribution

✍ Bradford R. Crain 📂 Article 📅 1979 🏛 Elsevier Science 🌐 English ⚖ 346 KB

Bivariate Density Estimation with Random

Bivariate Density Estimation with Randomly Truncated Data

✍ Ülkü Gürler; Kathryn Prewitt 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 220 KB

In this study bivariate kernel density estimators are considered when a component is subject to random truncation. In bivariate truncation models one observes the i.i.d. samples from the triplets (T, Y, X) only if T Y. In this set-up, Y is said to be left truncated by T and T is right truncated by Y