Some Statistical Properties of Functional Norms of Persistence Topological Landscapes

2020 ◽  
Author(s):  
Lloyd Leaverton ◽  
Yuri A. Katz ◽  
Josep Vives
Keyword(s):  
Statistical Properties

Statistical properties of type I intermittency

1982 ◽  
Vol 43 (4) ◽  
pp. 585-589 ◽  
Author(s):  
M. N. Bussac ◽  
C. Meunier
Keyword(s):  
Statistical Properties ◽  
Type I

Correlation in the heart rate data

1998 ◽  
Vol 2 ◽  
pp. 141-148
Author(s):  
J. Ulbikas ◽  
A. Čenys ◽  
D. Žemaitytė ◽  
G. Varoneckas
Keyword(s):  
Nonlinear Dynamics ◽  
Experimental Data ◽  
Heart Rate ◽  
Time Series ◽  
Cardiovascular Function ◽  
Statistical Properties ◽  
Rate Data ◽  
Heart Rate Data ◽  
Dynamical Nature ◽  
Analysis Of Time Series

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.

THE IMPACTS OF INDIVIDUAL INFORMATION ON LOSS RESERVING

2020 ◽  
pp. 1-45
Author(s):  
Zhigao Wang ◽  
Xianyi Wu ◽  
Chunjuan Qiu
Keyword(s):  
Information Model ◽  
Statistical Properties ◽  
Unknown Parameters ◽  
Asymptotic Behaviors ◽  
Computation Procedure ◽  
General Insurance ◽  
Loss Reserving ◽  
Portfolio Size ◽  
Better Than ◽  
Individual Information

Abstract The projection of outstanding liabilities caused by incurred losses or claims has played a fundamental role in general insurance operations. Loss reserving methods based on individual losses generally perform better than those based on aggregate losses. This study uses a parametric individual information model taking not only individual losses but also individual information such as age, gender, and so on from policies themselves into account. Based on this model, this study proposes a computation procedure for the projection of the outstanding liabilities, discusses the estimation and statistical properties of the unknown parameters, and explores the asymptotic behaviors of the resulting loss reserving as the portfolio size approaching infinity. Most importantly, this study demonstrates the benefits of individual information on loss reserving. Remarkably, the accuracy gained from individual information is much greater than that from considering individual losses. Therefore, it is highly recommended to use individual information in loss reserving in general insurance.

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