Regression analysis for current status data using the EM algorithm.
about
A flexible, computationally efficient method for fitting the proportional hazards model to interval-censored data.An Expectation Maximization algorithm for fitting the generalized odds-rate model to interval censored data.Semiparametric probit models with univariate and bivariate current-status data.Penalized estimation for proportional hazards models with current status data.Computationally Efficient Estimation for the Generalized Odds Rate Mixture Cure Model with Interval-Censored Data.
P2860
Regression analysis for current status data using the EM algorithm.
description
2013 nî lūn-bûn
@nan
2013 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Regression analysis for current status data using the EM algorithm.
@ast
Regression analysis for current status data using the EM algorithm.
@en
type
label
Regression analysis for current status data using the EM algorithm.
@ast
Regression analysis for current status data using the EM algorithm.
@en
prefLabel
Regression analysis for current status data using the EM algorithm.
@ast
Regression analysis for current status data using the EM algorithm.
@en
P2093
P2860
P356
P1476
Regression analysis for current status data using the EM algorithm.
@en
P2093
Christopher S McMahan
Joshua M Tebbs
Lianming Wang
P2860
P304
P356
10.1002/SIM.5863
P407
P577
2013-06-12T00:00:00Z