In this article, the weighted empirical likelihood is applied to a general setting of two-sample semiparametric models, which includes biased sampling models and case-control logistic regression models as special cases. For various types of censored data, such as right censored data, doubly censored data, interval censored data and partly interval-censored data, the weighted empirical likelihoo...

In practical applications of item response theory (IRT), item parameters are usually estimated first from a calibration sample. After treating these estimates as fixed and known, ability parameters are then estimated. However, the statistical inferences based on the estimated abilities can be misleading if the uncertainty of the item parameter estimates is ignored. Instead, estimated item param...

This paper gives a new approach for the maximum likelihood estimation of joint location and scale Cauchy distribution. We regard as single complex parameter derive form equation variable. Based on equation, we provide iterative scheme approximating estimate. also handle in an algebraic manner polynomial containing estimate root. provides another by root-finding algorithms polynomials, furthermo...

6.1 Spectral Estimation Methods 6.1.1 Bartlett Method 6.2 Minimum Variance Distortionless Response Estimator 6.3 Linear Prediction Method 6.4 Maximum Entropy Method 6.5 Maximum Likelihood Method 6.6 Eigenstructure Methods 6.7 MUSIC Algorithm 6.7.1 Spectral MUSIC 6.7.2 Root-MUSIC 6.7.3 Constrained MUSIC 6.7.4 Beam Space MUSIC 6.8 Minimum Norm Method 6.9 CLOSEST Method 6.10 ESPRIT Method 6.11 Wei...

Current methods used to analyze time to event data either rely on highly parametric assumptions which result in biased estimates of parameters which are purely chosen out of convenience, or are highly unstable because they ignore the global constraints of the true model. By using Targeted Maximum Likelihood Estimation (TMLE) one may consistently estimate parameters which directly answer the sta...