THE MEAN SQUARE RISK OF NONLINEAR REGULARIZATION IN THE PROBLEM OF INVERSION OF LINEAR HOMOGENEOUS OPERATORS WITH A RANDOM SAMPLE SIZE

2019 ◽  
Keyword(s):  
Sample Size ◽  
Random Sample ◽  
Mean Square ◽  
Random Sample Size ◽  
Nonlinear Regularization ◽  
The Mean ◽  
Homogeneous Operators

The Significance of Random Sample Size in Flow-Through Photometric Prescreening in Cervical Cytology

1976 ◽  
Vol 157 (2) ◽  
pp. 142-146 ◽  
Author(s):  
E. Sprenger ◽  
M. Schaden ◽  
D. Wagner ◽  
W. Sandritter
Keyword(s):  
Sample Size ◽  
Random Sample ◽  
Cervical Cytology ◽  
Random Sample Size ◽  
Flow Through

Limit theorems for extremes with random sample size

1998 ◽  
Vol 30 (03) ◽  
pp. 777-806 ◽  
Author(s):  
Dmitrii S. Silvestrov ◽  
Jozef L. Teugels
Keyword(s):  
Weak Convergence ◽  
Sample Size ◽  
Random Sample ◽  
Limit Theorems ◽  
Functional Limit ◽  
Functional Limit Theorems ◽  
Random Sample Size ◽  
Extremal Processes ◽  
Convergence Type

This paper is devoted to the investigation of limit theorems for extremes with random sample size under general dependence-independence conditions for samples and random sample size indexes. Limit theorems of weak convergence type are obtained as well as functional limit theorems for extremal processes with random sample size indexes.

scholarly journals On weak convergence of empirical processes for random number of independent stochastic vectors

1973 ◽  
Vol 73 (1) ◽  
pp. 139-144 ◽  
Author(s):  
Pranab Kumar Sen
Keyword(s):  
Weak Convergence ◽  
Sample Size ◽  
Random Sample ◽  
Random Number ◽  
Empirical Process ◽  
Empirical Processes ◽  
Random Sample Size ◽  
Martingale Property

AbstractBy the use of a semi-martingale property of the Kolmogorov supremum, the results of Pyke (6) on the weak convergence of the empirical process with random sample size are simplified and extended to the case of p(≥1)-dimensional stochastic vectors.

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