let x be a random variable from a normal distribution with unknown mean θ and known variance σ2. in many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. as the usual estimator of θ, i.e., x under the linex loss function is inadmissible, finding some competitors for x becomes worthwhile. the only study in the literature considered the problem of min...

We propose a jackknife for reducing the order of the bias of maximum likelihood estimates of nonlinear dynamic fixed effects panel models. In its simplest form, the half-panel jackknife, the estimator is just 2θ̂ − θ1/2, where θ̂ is the MLE from the full panel and θ1/2 is the average of the two half-panel MLEs, each using T/2 time periods and all N cross-sectional units. This estimator eliminates...

Motivated by a cancer survivorship program, this PhD thesis aims to develop methodology for risk assessment, classification, and prediction. We formulate the primary data collected from a cohort with two underlying categories, the at-risk and not-at-risk classes, using latent class models, and we conduct both cross-sectional and longitudinal analyses. We begin with a maximum pseudo-likelihood e...

In carcinogenicity experiments with animals where the tumor is not palpable it is common to observe only the time of death of the animal, the cause of death (the tumor or another independent cause, as sacrifice) and whether the tumor was present at the time of death. These last two indicator variables are evaluated after an autopsy. Defining the non-negative variables T1 (time of tumor onset), ...

This paper revisits the classical inference results for profile quasi maximum likelihood estimators (profile MLE) in the semiparametric estimation problem. We mainly focus on two prominent theorems: the Wilks phenomenon and Fisher expansion for the profile MLE are stated in a new fashion allowing finite samples and model misspecification. The method of study is also essentially different from t...

This paper considers the detection of a distributed target, which is important in high resolution radars (HRRs). We focus on the practical scenario where only partial observation is available. The key contribution of this work is the proposition of a generalized likelihood ratio test (GLRT) detector using matrix completion (MC). Firstly, a decision rule is obtained for the hypothesis test model...

We suggest censored maximum likelihood estimators for the first and second order parameters of a heavy tailed distribution by incorporating the second order regular variation into the censored likelihood function. This approach is different from the bias-reduced MLE proposed by Feuerverger & Hall (1999). In comparison with Feuerverger & Hall (1999), we derive the joint asymptotic limit for the ...

The maximum likelihood estimator (MLE) for a vehicle’s attitude using signals received from GPS satellites is derived in this paper. A statistical model of the measured phase double-differences is developed to form the likelihood function. The attitude is represented by a rotation matrix, a member of the group of 3×3 special orthogonal matrices. A steepest descent-like maximization algorithm is...

Evapotranspiration is arguably the least quantified component of hydrologic cycle. We propose two complementary strategies for estimation evapotranspiration rates and root water uptake profiles from soil-moisture sensor-array data. One our implementation ensemble Kalman filter (EnKF); it treats sink term in Richards equation, rather than soil moisture, as observable to update. The other a maxim...