Sentence examples for multivariable polynomials including from inspiring English sources

are a unification (and generalization) of several known families of multivariable polynomials including (for example) Chan-Chyan-Srivastava polynomials g n ( α 1, …, α r ) ( x 1, …, x r ).

Again, by suitably specializing the coefficient of the first class of multivariable polynomials, it can be reduced to other multivariable hypergeometric polynomials and classical orthogonal polynomials of one or more variables.

In this paper, we obtain a Schläfli's type contour integral representation for the multivariable polynomials given in (1.9).

As homogeneous multivariable polynomials, we can restrict (y_{k}) to a ball; that is, (|y_{k}|=1).

In this section, we prove two theorems on composition of the Marichev-Saigo-Maeda operators with the product of a multivariable H-function and the first class of multivariable polynomials.

The main object of the present paper is to establish new fractional integral formulas (of Marichev-Saigo-Maeda type) involving the products of the multivariable H-functions and the first class of multivariable polynomials due to Srivastava and Garg.

As can be seen, the above game problem (14) is reduced to a finite number of maximization problems in which low order multivariable polynomials are maximized over boxes.

The non-linear models include artificial neural networks (ANNs) and multivariable polynomial regression.

According to these results, we built a multivariable model including the SOFA score, INR, and RRT.

Multivariable analyses, including computation of least squares (LS) means and standard errors (SEs) were done using general linear models [34].

Despite our attempt to overcome confounding by using multivariable models including well-established confounders, unmeasured residual confounding may have occurred.