Generalization of Szász operators: quantitative estimate and bounded variation

Difference of exponential type Szász and Szász-Kantorovich operators is obtained. Similar estimates are given for higher order $\mu$-derivatives of the Szász operators and the Szász-Kantorovich type operators acting on the same order $\mu$-derivative of the function. These differences are given in quantitative form using first modulus of continuity. Convergence in variation of the operators in the space of functions with bounded variation with respect to the variation seminorm is obtained. The results propose a general framework covering the results provided by previous literature.

Generalized Bernstein Kantorovich operators: Voronovskaya type results, convergence in variation

This paper includes Voronovskaya type results and convergence in variation for the exponential Bernstein Kantorovich operators. The Voronovskaya type result is accompanied by a relation between the mentioned operators and suitable auxiliary discrete operators. Convergence of the operators with respect to the variation seminorm is obtained in the space of functions with bounded variation. We propose a general framework covering the results provided by previous literature.

Influence and Information in Team Decisions: Evidence from Medical Residency

I study team decisions among physician trainees. Exploiting a discontinuity in team roles across trainee tenure, I find evidence that teams alter decision-making, concentrating influence in the hands of senior trainees. I also demonstrate little convergence in variation of trainee effects despite intensive training. This general pattern of trainee effects on team decision-making exists in all types of decisions and settings that I examine. In analyses evaluating mechanisms behind this pattern, I find support for the idea that significant experiential learning occurs during training and that teams place more weight on judgments of senior trainees in order to aggregate information. (JEL D83, I11, J44, M53, M54)

On convergence and compactness in variation with shift of discrete probability laws

We consider a class of discrete distribution functions, whose characteristic functions are separated from zero, i. e. their absolute values are greater than positive constant on the real line. The class is rather wide, because it contains discrete infinitely divisible distribution functions, functions of lattice distributions, whose characteristic functions have no zeroes on the real line, and also distribution functions with a jump greater than 1/2. Recently the authors showed that characteristic functions of elements of this class admit the Lévy-Khinchine type representations with non-monotonic spectral function. Thus our class is included in the set of so called quasi-infinitely divisible distribution functions. Using these representation the authors also obtained limit and compactness theorems with convergence in variation for the sequences from this class. This note is devoted to similar results concerning convergence and compactness but with weakened convergence in variation. Replacing of type of convergence notably expands applicability of the results.

Approximation by sampling-type nonlinear discrete operators in φ-variation

In the present paper, our purpose is to obtain a nonlinear approximation by using convergence in ?-variation. Angeloni and Vinti prove some approximation results considering linear sampling-type discrete operators. These types of operators have close relationships with generalized sampling series. By improving Angeloni and Vinti?s one, we aim to get a nonlinear approximation which is also generalized by means of summability process. We also evaluate the rate of approximation under appropriate Lipschitz classes of ?-absolutely continuous functions. Finally, we give some examples of kernels, which fulfill our kernel assumptions.