Contiguity, Entire Separation, Convergence in Variation

2003 ◽  
pp. 284-323
Author(s):  
Jean Jacod ◽  
Albert N. Shiryaev
Keyword(s):  
Convergence In Variation

Influence and Information in Team Decisions: Evidence from Medical Residency

2021 ◽  
Vol 13 (1) ◽  
pp. 106-137
Author(s):  
David C. Chan
Keyword(s):  
Decision Making ◽  
Experiential Learning ◽  
General Pattern ◽  
Medical Residency ◽  
Team Decision Making ◽  
Intensive Training ◽  
Aggregate Information ◽  
Convergence In Variation ◽  
Study Team ◽  
Team Decision

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)

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

2021 ◽  
Vol 8 (3) ◽  
pp. 385-393
Author(s):  
Ivan A. Alexeev ◽  
◽  
Alexey A. Khartov ◽  
Keyword(s):  
Real Line ◽  
Discrete Distribution ◽  
Distribution Functions ◽  
Divisible Distribution ◽  
Characteristic Functions ◽  
Infinitely Divisible Distribution ◽  
Infinitely Divisible ◽  
The Real ◽  
Convergence In Variation ◽  
Compactness Theorems

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.

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