Regression M-estimators with doubly censored data
نویسندگان
چکیده
منابع مشابه
Regression analysis of doubly censored failure time data with frailty.
In doubly censored failure time data, the survival time of interest is defined as the elapsed time between an initial event and a subsequent event, and the occurrences of both events cannot be observed exactly. Instead, only right- or interval-censored observations on the occurrence times are available. For the analysis of such data, a number of methods have been proposed under the assumption t...
متن کاملSimultaneous marginal survival estimators when doubly censored data is present.
A doubly censoring scheme occurs when the lifetimes T being measured,from a well-known time origin, are exactly observed within a window [L, R] of observational time and are otherwise censored either from above (right-censored observations)or below (left-censored observations). Sample data consists on the pairs (U, δ)where U = min{R, max{T, L}} and δ indicates whether T is exactly observed (δ =...
متن کاملNonlinear Regression With Censored Data
Suppose the random vector (X,Y ) satisfies the regression model Y = m(X) + σ(X)ε, where m(·) = E(Y |·) belongs to some parametric class {mθ(·) : θ ∈ Θ} of regression functions, σ2(·) = Var(Y |·) is unknown, and ε is independent of X. The response Y is subject to random right censoring, and the covariate X is completely observed. A new estimation procedure for the true, unknown parameter vector ...
متن کاملTracking Interval for Doubly Censored Data with Application of Plasma Droplet Spread Samples
Doubly censoring scheme, which includes left as well as right censored observations, is frequently observed in practical studies. In this paper we introduce a new interval say tracking interval for comparing the two rival models when the data are doubly censored. We obtain the asymptotic properties of maximum likelihood estimator under doubly censored data and drive a statistic for testing the ...
متن کاملRobust Regression with Projection Based M-estimators
The robust regression techniques in the RANSAC family are popular today in computer vision, but their performance depends on a user supplied threshold. We eliminate this drawback of RANSAC by reformulating another robust method, the M-estimator, as a projection pursuit optimization problem. The projection based pbM-estimator automatically derives the threshold from univariate kernel density est...
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: The Annals of Statistics
سال: 1997
ISSN: 0090-5364
DOI: 10.1214/aos/1030741089