This letter introduces a novel rigid point set registration (PSR) approach that accurately aligns the pre-operative space and intra-operative together in scenario of computer-assisted orthopedic surgery (CAOS). Motivated by considering anisotropic positional localization noise utilizing undirected normal vectors sets (PSs), multi-variate Gaussian distribution Watson are utilized to model vector...

Generalized Birnbaum-Saunders (GBS) distributions are proposed by Díaz-García et al. ([15], [16]) based on the family of elliptically contoured univariate distributions. This model is well-known as the highly flexible lifetime model by the difference in the degrees of kurtosis and asymmetry and processes uni-modality and bimodality. In this paper, a modifier Chi-squared goodness-of-fit test bas...

We present MEMLET (MATLAB-enabled maximum-likelihood estimation tool), a simple-to-use and powerful program for utilizing maximum-likelihood estimation (MLE) for parameter estimation from data produced by single-molecule and other biophysical experiments. The program is written in MATLAB and includes a graphical user interface, making it simple to integrate into the existing workflows of many u...

A problem of estimating the location of a source of scattered radiation is considered. The role of extremes in estimation problems for truncated distributions is discussed from the Bayesian point of view. The emphasis is made on the bivariate case of spherically symmetric distributions. The cases of truncated normal, uniform, and Cauchy distributions are considered. Such location estimators as ...

We study exponential families of distributions that are multivariate totally positive order 2 (MTP2), show these convex and derive conditions for existence the MLE. Quadratic familes MTP2 contain attractive Gaussian graphical models ferromagnetic Ising as special examples. defined by intersecting space canonical parameters with a polyhedral cone whose faces correspond to conditional independenc...

We review statistical methodology for estimating mean concentrations of potentially toxic pollutants in water, for small samples that are not normally distributed and often contain substantial numbers of nondetects, i.e. samples that are only known to be below some set of fixed thresholds. Maximum likelihood estimation (MLE) and regression on order statistics (ROS) are two main approaches that ...

In this paper, we introduce the exponentiated generalized alpha power family of distributions to extend several other distributions. We used new discuss exponential (EGAPEx) distribution. Some statistical properties EGAPEx distribution are obtained. The model parameters obtained by maximum likelihood estimation (MLE), product spacing (MPS) and Bayesian methods. A Monte Carlo Simulation is perfo...

While differencing transformations can eliminate nonstationarity, they typically reduce signal strength and correspondingly reduce rates of convergence in unit root autoregressions. The present paper shows that aggregating moment conditions that are formulated in differences provides an orderly mechanism for preserving information and signal strength in autoregressions with some very desirable ...

In many of the possible applications as well as the theoretical models of computational social choice, the agents’ preferences are represented as partial orders. In this paper, we extend the maximum likelihood approach for defining “optimal” voting rules to this setting. We consider distributions in which the pairwise comparisons/incomparabilities between alternatives are drawn i.i.d. We call s...

We consider a general multivariate model where univariate marginal distributions are known up to a common parameter vector and we are interested in estimating that vector without assuming anything about the joint distribution, except for the marginals. If we assume independence between the marginals and maximize the resulting quasilikelihood, we obtain a consistent but inefficient estimate. If ...