Search results for: A.I. Khuri

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article

Approximating moments of continuous functions of random variables using Bernstein polynomials

A.I. Khuri, S. Mukhopadhyay, M.A. Khuri

Statistical Methodology > 2015 > 24 > Complete > 37-51

Bernstein polynomials have many interesting properties. In statistics, they were mainly used to estimate density functions and regression relationships. The main objective of this paper is to promote further use of Bernstein polynomials in statistics. This includes (1) providing a high-level approximation of the moments of a continuous function g(X) of a random variable X, and (2) proving Jensen’s...

article

Comparison of designs for generalized linear models under model misspecification

S. Mukhopadhyay, A.I. Khuri

Statistical Methodology > 2012 > 9 > 3 > 285-304

The purpose of this article is to demonstrate the use of the quantile dispersion graphs (QDGs) approach for comparing candidate designs for generalized linear models in the presence of model misspecification in the linear predictor. The proposed design criterion is based on the mean-squared error of prediction which incorporates the prediction variance and the bias caused by fitting the wrong model...

article

Optimization in a multivariate generalized linear model situation

S. Mukhopadhyay, A.I. Khuri

Computational Statistics and Data Analysis > 2008 > 52 > 10 > 4625-4634

The purpose of this article is to find the settings of the factors which simultaneously optimize several mean responses in a multivariate generalized linear model (GLM) environment. The generalized distance approach, initially developed for the simultaneous optimization of several linear response surface models, is adapted to this multivariate GLM situation. An application of the proposed methodology...

article

Comparison of designs for multivariate generalized linear models

S. Mukhopadhyay, A.I. Khuri

Journal of Statistical Planning and Inference > 2008 > 138 > 1 > 169-183

The purpose of this paper is to discuss response surface designs for multivariate generalized linear models (GLMs). Such models are considered whenever several response variables can be measured for each setting of a group of control variables, and the response variables are adequately represented by GLMs. The mean-squared error of prediction (MSEP) matrix is used to assess the quality of prediction...

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Keywords

MEAN-SQUARED ERROR OF PREDICTION (2)
BALANCED AND UNBALANCED DATA (1)
BIVARIATE BINARY DISTRIBUTION (1)
DELTA METHOD (1)
HERITABILITY FUNCTION (1)
JENSEN’S INEQUALITY (1)
KRIGING (1)
LINEAR PREDICTOR (1)
MODEL BIAS (1)
POLYNOMIAL APPROXIMATION (1)
PREDICTION BIAS (1)
PREDICTION VARIANCE (1)
QUANTILE DISPERSION GRAPHS (1)
QUANTILES OF THE MEAN-SQUARED ERROR OF PREDICTION (1)
RESPONSE SURFACE DESIGN (1)
RESPONSE SURFACE METHODOLOGY (1)
TCHEBYCHEFF POLYNOMIALS (1)
UNIFORM CONVERGENCE (1)
WEIERSTRASS APPROXIMATION THEOREM (1)
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Search results for: A.I. Khuri

Approximating moments of continuous functions of random variables using Bernstein polynomials

Comparison of designs for generalized linear models under model misspecification

Optimization in a multivariate generalized linear model situation

Comparison of designs for multivariate generalized linear models

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