Let $\go{g}$ be a finite-dimensional semi-simple Lie algebra, $\go{h}$ a Cartan subalgebra of $\go{g}$, and $W$ its Weyl group. The group $W$ acts diagonally on $V:=\go{h}\oplus\go{h}^*$, as well as on $\mathbb{C}[V]$. The purpose of this article is to study the Poisson homology of the algebra of invariants $\mathbb{C}[V]^W$ endowed with the standard symplectic bracket. To begin with, we give g...

When the observed data are imprecise, uncertain regression model is more suitable for linear analysis. Least squares estimation can fully consider given and minimize sum of residual error effectively solve equation imprecisely data. On basis uncertainty theory, this paper presents an deformation method solving unknown parameters in equations. We first establish one-dimensional then extend it to...

Abstract Stem profile needs to be modeled with an accurate taper equation produce reliable tree volume assessments. We propose a semiparametric method where few priori functional form assumptions or parametric specification are required. compared the diameter and predictions of penalized spline regression (P-spline), P-spline extended additive dbh-class variable, six alternative equations inclu...

rice husk ash (rha) is natural pozzolan containing reactive silica and/or aluminum. when the material is mixed with lime in powdered form and in the presence of water, it will set and harden like cement. this work uses osadebe’s optimization model to optimize the shear modulus of concrete made from rha. the strengths predicted by the model are in good agreement with their corresponding experime...

Regression analysis is used to predict the dependent variables individually concerning the explanatory available variables and find out the “best fit” line or curve through a series of data in a graph. It is also minimizing the sum of the squares deviations of any experimental data points from the theoretical curve. An important aspect of this analysis is to ensure that the x values are as accu...

Orthogonal regression is one of the standard linear regression methods to correct for the eeects of measurement error in predictors. We argue that orthogonal regression is often misused in errors-in-variables linear regression, because of a failure to account for equation errors. The typical result is to overcorrect for measurement error, i.e., overestimate the slope, because equation error is ...

This paper describes a new method for creating polynomial regression models. The new method is compared with stepwise regression and symbolic regression using three example problems. The first example is a polynomial equation. The two examples that follow are real-world problems, approximating the Colebrook–White equation and rainfall-runoff modelling. The three example problems illustrate the ...

We examine the relative roles of marketing actions and product quality in determining commercial success. Using the motion picture context, in which product quality is difficult for consumers to anticipate and information on product success is available for different points in time, we model the effects of studio actions and movie quality on a movie’s sales during different phases of its theatr...

Purpose – The purpose of this paper is to present an empirical investigation of the critical determinants for the adoption of e-market in Australian small-and-medium sized enterprises (SMEs) within the technology-organization-environment (TOE) framework. Design/methodology/approach – A conceptual model is proposed for better understanding the adoption of e-market in Australian SMEs. Structural ...

OBJECTIVES To assess the accuracy with which clinicians estimate premorbid IQ from demographic variables and compare it with a regression equation which uses the same information. DESIGN Repeated measures and correlational. METHODS Sixty participants were administered the WAIS-R and had their demographic variables recorded (age, sex, years of education and occupation). Eight clinical psycho...