In this paper it is shown that the use of non singular block invariant ma trices of covariates leads to generalized estimating equations estimators GEE estimators Liang K Y Zeger S Biometrika which are identical regardless of the working correlation matrix used Moreover they are e cient McCullagh P The Annals of Statistics If on the other hand only time invariant covari ates are used the e cien...

We analyze an augmented inverse probability of non-missingness weighted estimator of a survival function for a missing censoring indicator model, in the absence and presence of left truncation. The estimator improves upon its precursor but is still not the best in terms of achieving minimal asymptotic variance.

In the one-parameter regression model with AR(1) and AR(2) errors we find explicit expressions and a continuous approximation of the optimal discrete design for the signed least square estimator. The results are used to derive the optimal variance of the best linear estimator in the continuous time model and to construct efficient estimators and corresponding optimal designs for finite samples.

The Local Cosine Decomposition of Coifman and Wickerhauser 1] is modiied by incorporating two degrees of freedom that increase the adaptability of the best basis. These are relative shifts between resolution levels and adaptive polarity foldings. The resultant expansion is shift-invariant, and yields adaptive time-frequency distributions which are characterized by high resolution, high concentr...

In this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against th...

Consider testing normality against a one-parameter family of univariate distributions containing the normal distribution as the boundary, e.g., the family of t-distributions or an infinitely divisible family with finite variance. We prove that under mild regularity conditions, the sample skewness is the locally best invariant (LBI) test of normality against a wide class of asymmetric families a...

The matching of two-dimensional shapes is an important problem with applications in domains as diverse as biometrics, industry, medicine and zoology. The distance measure used must be invariant to many distortions, including scale, offset, noise, partial occlusion, etc. Most of these distortions are relatively easy to handle, either in the representation of the data or in the similarity measure...

This paper describes a novel correct phoneme sequence estimation method that uses a recurrent neural network (RNN)-based framework for spoken term detection (STD). In an automatic speech recognition (ASR)-based STD framework, ASR performance (word or subword error rate) affects STD performance. Therefore, it is important to reduce ASR errors to obtain good STD results. In this study, we use an ...

This paper studies design schemes for the X control chart under non-normality. Different estimators of the standard deviation are considered and the effect of the estimator on the performance of the control chart under non-normality is investigated. Two situations are distinguished. In the first situation, the effect of non-normality on the X control chart is investigated by using the control l...

Abstract. For the given data (wi, xi, yi), i = 1, . . . , n, and the given model function f(x;θ), where θ is a vector of unknown parameters, the goal of regression analysis is to obtain estimator θ∗ of the unknown parameters θ such that the vector of residuals is minimized in some sense. The common approach to this problem of minimization is the least-squares method, that is minimizing the L2 n...