Nonparametric tests for multiple regression under progressive censoring
نویسندگان
چکیده
منابع مشابه
Nonparametric quantile estimation under progressive censoring
This work deals with asymptotic properties of the [αm]-th order statistic of a type-II progressively censored sample of size m. Such an order statistic, indexed by α ∈ [0, 1], is called the quantile process. Our main results concern the normalized version of the quantile process for which invariance principles are obtained. These results are applied in order to construct non-parametric estimato...
متن کاملNonparametric Testing for Simple Regression under Progressive Censoring with Staggering Entry and Random Withdrawal
In the context of (multi-center) clinical trials and life testing problems, a general model incorporating both the staggering entry and random withdrawal and pertaining to a simple regression problem (including the two-sample location problem as a special case) is conceived, and, within this framework, a scheme allowing progressive censoring (continuous monitoring of experimentation from the be...
متن کاملNonparametric Predictive Comparison of Lifetime Data under Progressive Censoring
In reliability and lifetime testing, comparison of two groups of data is a common problem. In some lifetime experiments, making a quick and efficient decision is desirable in order to save time and costs. To this end, a progressive censoring scheme can be useful, with censoring occurring at different stages [2]. This paper presents a nonparametric predictive inference (NPI) approach to compare ...
متن کاملGeneralized Rank Tests for Progressive Censoring Procedures
In clinical trials and life testing problems the responses are time-sequential in nature and a compl~t~ experimentation may involve a prohibitive amount of time and cost •. • Fo't "this reason, progressive· censoring schemes (PCS) are often advocated with a view to terminating the experimentation at the earliest possible stage if the accumulated statistical evidence warrants to do so. In this d...
متن کاملNonparametric Regression Estimation under Kernel Polynomial Model for Unstructured Data
The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framewo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 1978
ISSN: 0047-259X
DOI: 10.1016/0047-259x(78)90021-0