In this paper we assume that the life time of a test unit follows a log-logistic distribution with known scale parameter. Tables of optimum times of changing stress level for simple step-stress plans under a cumulative exposure model are obtained by minimizing the asymptotic variance of the maximum likelihood estimator of the model parameters at the design stress with respect to the change time...

In linear regression, we need to avoid adding too much richness to the model. Therefore we need feature selection, or regularization to make our fitting curve smoother. Qualitatively, the original linear regression model is an optimization problem of the form min w m i=1 (w · x i − y i) 2 And the corresponding regularized version of the same problem is min w m i=1 (w · x i − y i) 2 + λw 2 2 , w...

Under left truncation, data (X(i), Y(i)) are observed only when Y(i) ≤ X(i). Usually, the distribution function F of the X(i) is the target of interest. In this paper, we study linear functionals ∫ φ dF(n) of the nonparametric maximum likelihood estimator (MLE) of F, the Lynden-Bell estimator F(n). A useful representation of ∫ φ dF(n) is derived which yields asymptotic normality under optimal m...

In this paper, we propose two time of arrival estimators for ultra wideband signals based on the phase difference between the discrete Fourier transforms (DFT) of the transmitted and received signals. The first estimator is based on the slope of the unwrapped phase and the second one on the absolute unwrapped phase. We derive the statistics of the unwrapped phase. We show that slope-based estim...

Mixed linear models are used to analyse data in many settings. These models generally rely on the normality assumption and are often fitted by means of the maximum likelihood estimator (MLE) or the restricted maximum likelihood estimator (REML). However, the sensitivity of these estimation techniques and related tests to this underlying assumption has been identified as a weakness that can even...

Hidden Markov models were successfully applied in various fields of time series analysis, especially for analyzing ion channel recordings. The maximum likelihood estimator (MLE) has recently been proven to be asymptotically normally distributed. Here, we investigate finite sample properties of the MLE and of different types of likelihood ratio tests (LRTs) by means of simulation studies. The ML...

The reputation of the maximum pseudolikelihood estimator (MPLE) for Exponential Random Graph Models (ERGM) has undergone a drastic change over past 30 years. While first receiving broad support, mainly due to its computational feasibility and lack alternatives, general opinions started with introduction approximate likelihood (MLE) methods that became practicable increasing computing power MCMC...

We study two linear estimators for stationary invertible VARMA models in echelon form (for identification), with known Kronecker indices. Such linear estimators are much simpler to compute than Gaussian maximum likelihood (ML) estimators often proposed for such models, which are highly nonlinear. The first estimator is an improved two-step estimator which can be interpreted as a generalized lea...