Quasi-Newton methods for numerical optimization exploit quadratic Taylor polynomial models of the objective function. Trust regions are widely used to ensure the global convergence of these methods. Analogously, response surface methods for stochastic optimization exploit linear and quadratic regression models of the objective function. Ridge analysis is widely used to safeguard the optimizatio...

This paper considers estimation of the intercept and slope vector parameters of the simple multivariate linear regression model with Student-t errors in the presence of uncertain prior information on the value of the unknown slope vector. The unrestricted, restricted, preliminary test, shrinkage, and positive-rule shrinkage estimators are defined together with the expressions for the bias, quad...

BACKGROUND Multiple imputation is often used for missing data. When a model contains as covariates more than one function of a variable, it is not obvious how best to impute missing values in these covariates. Consider a regression with outcome Y and covariates X and X2. In 'passive imputation' a value X* is imputed for X and then X2 is imputed as (X*)2. A recent proposal is to treat X2 as 'jus...

The study pertains to the estimation of carcass traits of broiler duck reared in hot and humid climate of Eastern India. The carcass and different cut weights were estimated using non invasive measurements, breast angle and body weights separately at different ages, i.e. 21, 28,35,42,49 and 56 days of age. The carcass traits were estimated using linear, logarithmic, exponential, inverse, power,...

We present a novel approach for the inverse problem in electrical impedance tomography based on regularized quadratic regression. Our contribution introduces a new formulation for the forward model in the form of a nonlinear integral transform, that maps changes in the electrical properties of a domain to their respective variations in boundary data. Using perturbation theory results the kernel...

This paper describes an algorithm for cardinality-constrained quadratic optimization problems, which are convex quadratic programming problems with a limit on the number of non-zeros in the optimal solution. In particular, we consider problems of subset selection in regression and portfolio selection in asset management and propose branch-and-bound based algorithms that take advantage of the sp...

replacement of a tractor is an influential factor affecting timely farm operation. the accurate prediction of repair and maintenance costs is essential to selection of a replacement model. this study used empirical data for 60 two-wheel drive (2wd) tractors from astan ghods-e razavi agroindustry. the types and numbers of tractors used were the massey ferguson 285 (17), fiat (10), john deere 314...

SUMMARY – An ActiveX component to calculate temperature and vapour fraction in a geothermal reservoir using the quartz solubility geothermometry was written in Visual Basic. The approach is based on the conservation of mass and energy (enthalpy). Four representative types of regression equations for quartz solubility: (i) a quadratic regression equation of 1/T and pressure P, (ii) a linear equa...

In this work, we propose a new semi-supervised algorithm for remotely sensed hyperspectral image classification which belongs to the family of multiple classifier systems. The proposed approach combines the output of two well-established discriminative classifiers: sparse multinomial logistic regression (SMLR) and quadratic discriminant analysis (QDA). Our approach follows a two-step strategy. ...

We derive the matrix that minimizes a quadratic criterion subject to linear equality constraints. Since we do not assume that the matrix of the quadratic form criterion is nonsingular, our optimization result is more general than those previously published. We make use of the extended result of this paper to (i) obtain the best linear unbiased estimate of the parameters in a linear regression w...