Likelihood Estimation with Incomplete Array Variate Observations
نویسنده
چکیده
Missing data present an important challenge when dealing with high dimensional data arranged in the form of an array. In this paper, we propose methods for estimation of the parameters of array variate normal probability model from partially observed multi-way data. The methods developed here are useful for missing data imputation, estimation of mean and covariance parameters for multi-way data. A multi-way semiparametric mixed effects model that allows separation of multi-way covariance effects is also defined and an efficient algorithm for estimation based on the spectral decompositions of the covariance parameters is recommended. We demonstrate our methods with simulations and with real life data involving the estimation of genotype and environment interaction effects on possibly correlated traits.
منابع مشابه
Windowing Effects of Short Time Fourier Transform on Wideband Array Signal Processing Using Maximum Likelihood Estimation
During the last two decades, Maximum Likelihood estimation (ML) has been used to determine Direction Of Arrival (DOA) and signals propagated by the sources, using narrowband array signals. The algorithm fails in the case of wideband signals. As an attempt by the present study to overcome the problem, the array outputs are transformed into narrowband frequency bins, using short time Fourier tran...
متن کاملWindowing Effects of Short Time Fourier Transform on Wideband Array Signal Processing Using Maximum Likelihood Estimation
During the last two decades, Maximum Likelihood estimation (ML) has been used to determine Direction Of Arrival (DOA) and signals propagated by the sources, using narrowband array signals. The algorithm fails in the case of wideband signals. As an attempt by the present study to overcome the problem, the array outputs are transformed into narrowband frequency bins, using short time Fourier tran...
متن کاملImproving the Performance of Bayesian Estimation Methods in Estimations of Shift Point and Comparison with MLE Approach
A Bayesian analysis is used to detect a change-point in a sequence of independent random variables from exponential distributions. In This paper, we try to estimate change point which occurs in any sequence of independent exponential observations. The Bayes estimators are derived for change point, the rate of exponential distribution before shift and the rate of exponential distribution after s...
متن کاملComparative assessment of the accuracy of maximum likelihood and correlated signal enhancement algorithm positioning methods in gamma camera with large square photomultiplier tubes
Introduction: The gamma cameras, based on scintillation crystal followed by an array of photomultiplier tubes (PMTs), play a crucial role in nuclear medicine. The use of square PMTs provides the minimum dead zones in the camera. The camera with square PMTs also reduces the number of PMTs relative to the detection area. Introduction of a positioning algorithm to improve the spat...
متن کاملDetection of Outliers and Influential Observations in Linear Ridge Measurement Error Models with Stochastic Linear Restrictions
The aim of this paper is to propose some diagnostic methods in linear ridge measurement error models with stochastic linear restrictions using the corrected likelihood. Based on the bias-corrected estimation of model parameters, diagnostic measures are developed to identify outlying and influential observations. In addition, we derive the corrected score test statistic for outliers detection ba...
متن کامل