Stancu Type Baskakov—Durrmeyer Operators and Approximation Properties

: In this article, we introduce Stancu type generalization of Baskakov–Durrmeyer operators by using inverse Pólya–Eggenberger distribution. We discuss some basic results and approximation properties. Moreover, we study the statistical convergence for these operators.


Preliminaries and Introduction
The approximation of functions by positive linear operators is an important research area in the classical approximation theory. It provides us key tools for exploring the computer-aided geometric design, numerical analysis and the solutions of ordinary and partial differential equations that arise in the mathematical modeling of real world phenomena. In the last four decades, several operators have been modified and their approximation properties has been discussed in real and complex domain.
A fundamental result in development of functions approximation theory is known as First Weierstrass approximation theorem, given by K. Weierstrass [1] in 1885, namely: for any function h ∈ C[a, b] and ε > 0, there exists an algebraic polynomial P(x) with real coefficients, such that |h(u) − P(u)| < ε, for any u ∈ [a, b], where C[0, 1] is the space of all continuous functions defined on [0, 1]. The first proof of the Weierstrass approximation theorem was long and complicated, and provoked many famous mathematicians to find simpler and more instructive proofs. In 1905, E. Borel [2] proposed determination of an interpolation process, that allows finding polynomials P(u), which converge uniformly to the function h ∈ C[a, b] . In 1912, S.N. Bernstein was able to give an outstanding solution for the problem proposed by E. Borel.
In [3], Bernstein polynomial was proposed to provide an easy and elegant proof of the famous Weierstrass theorem which is defined by To deal with Lebesgue integrable functions, for which Bernstein operators are unsuitable, Kantorovich [4] studied the following operators: were introduced by Mirakjan [5] and Szász [6]. Durrmeyer [7] proposed Since then a large number of such operators have been introduced to approximate functions of different classes in different settings and spaces. One of such operators are the Baskakov operators [8] defined by The Pólya-Eggenberger distribution (P-E) and the inverse Pólya-Eggenberger (I-P-E) (see [9]) are defined by r = 0, 1, 2, ..., m. Stancu [10] constructed new operators by using the Pólya-Eggenberger distribution (P-E) (6).
Further, in 1970, Stancu [11] introduced the following operators using (I-P-E) distribution (7) (1+u) [r+j,−α] . For α = 0, operators (9) are reduced to (5). For the operators based on (P-E) distribution, one can see the details in [12][13][14]. Gupta et al. [15] introduced Durrmeyer type modification of (9) as follows: Approximation theory is very crucial subject which is used in various fields by researchers. In which of them, a part of approximation theory is linear positive operators having an important role for studying various properties. There has been an extensive study on the approximation by these operators. Many mathematicians has inspired so far from past.
The computation of the test functions by Stancu operators was done long time ago and can be found in [10]. Based on the fact that many properties of Bernstein operators can be transferred to the Stancu operators (see [16][17][18]), we define Stancu type generalization of Baskakov type Pólya-Durrmeyer operators (10) as follows: where λ, µ are any non negative real numbers such that λ ≤ µ . If λ = µ = 0, the operators (11) reduce to (10).

Basic Results
The following results will be needed.
and β(l, p), l, p > 0 is the Beta function of second kind.
Proof. We use the relationship where β(l, p) and Γ(r)(r > 0) are defined by By simple calculation, we get By the definition of Γ, we obtain Proof. Using Lemma 1 for r = 0, 1, 2, we have Using Equality (i) first moment can be found trivially. Also, by using Equality (ii), we get Finally, using Equality (iii), we have

Approximation Properties
Having a sequence of operators which approximate a given function arises the question of evaluation of the committed error. This is given by the approximation order, which depends on the smoothness properties of functions. In estimates of the approximation degree a convenient tool for measuring the smoothness of functions is represented by the modulus of continuity. The next question is: how can we evaluate the committed error in the function approximation process? A convenient tool is the modulus of continuity. Another important tool for evaluating of the committed error is the modulus of smoothness of second order. Estimates using combinations of first and second order modulus of smoothness are more refined then estimates using only the modulus of continuity. Let Further, consider the K 2 -functional: There is an absolute constant C > 0 such that (see Devore and Lorentz [19], p. 177, Theorem 2.4) where ω 2 (h, are respectively the usual and second order modulus of continuity of h ∈ C B [0, ∞).
Let τ ∈ W 2 ∞ and x, t ∈ [0, ∞). Then from the Taylor's expansion, we get Taking infimum over all τ ∈ W 2 , we get In view of (12), Hence the proof.
The Lipschitz type space is defined by where M > 0 and 0 < γ ≤ 1.