the topological index of a graph g is a numeric quantity related to g which is invariant underautomorphisms of g. the vertex pi polynomial is defined as piv (g)  euv nu (e)  nv (e).then omega polynomial (g,x) for counting qoc strips in g is defined as (g,x) =cm(g,c)xc with m(g,c) being the number of strips of length c. in this paper, a new infiniteclass of fullerenes is constructed. the ...

Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improvin...

This paper proposes a target cost function for F0 based on polynomial regression for use in concatenative speech synthesis. Polynomial regression is used to express the time series of F0 continuously, and remove effects of microprosody. We conducted a perceptual experiment and confirmed that the proposed function provides a higher correlation with perceptual scores than does the conventionally ...

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...

One of the essential sectors of Myanmar economy is agriculture which is sensitive to climate variation. The most important climatic element which impacts on agriculture sector is rainfall. Thus rainfall prediction becomes an important issue in agriculture country. Multi variables polynomial regression (MPR) provides an effective way to describe complex nonlinear input output relationships so th...

Linear regression models are among the models most used in practice, although the practitioners are often not sure whether their assumed linear regression model is at least approximately true. In such situations, only designs for which the linear model can be checked are accepted in practice. For important linear regression models such as polynomial regression, optimal designs do not have this ...

A fast algorithm for calculating the simplicial depth of a single parameter value of a polynomial regression model and for calculating the maximum simplicial depth within an affine subspace of the parameter space or a polyhedron is presented. Since the maximum simplicial depth estimator is not unique, l1 and l2 methods are used to make the estimator unique. This estimator is compared with other...