Inverse Sampling for Bivariate Nonparametric Two-Sample Problems Against Restricted Alternatives

1992 ◽  
Vol 42 (3-4) ◽  
pp. 221-236 ◽  
Author(s):  
Uttam Bandyopadhyay ◽  
Gopaldeb Chattopadhyay
Keyword(s):  
Nonparametric Tests ◽  
Bivariate Distribution ◽  
Distribution Functions ◽  
Subject Classification ◽  
Fixed Size ◽  
Inverse Sampling ◽  
Large Sample ◽  
Ams Subject Classification

The object of the present investigation is to provide suitable nonparametric tests for testing the identity of two bivariate distribution functions F1 and F2 against a class of restricted alternatives when there is sample of fixed size m from F1 and the observations from F2 are drawn sequentially. Various large sample results of the proposed tests are formulated and examined. AMS Subject Classification: Primary 62010, Secondary 62020.

Semi–Sequential Nonparametric Tests for two Populations with one Sample Size Fixfd

1980 ◽  
Vol 29 (1-2) ◽  
pp. 45-64 ◽  
Author(s):  
Uttam Bandyopadhyay
Keyword(s):  
Sample Size ◽  
Nonparametric Tests ◽  
Fixed Size ◽  
Large Sample ◽  
The Right ◽  
The Given ◽  
Two Populations ◽  
Space Observations

The problem or testing the identity of two populations given a sample of fixed size from the first population, is considered . The given sample is used to demarcate a suitable region in the observational space. Observations are then drawn sequentially from the second population. At each step the number of observations lying in the demarcated region is counted and rejection is indicated if this number deviates too much (in the right direction) Otherwise, observation is continued till a prefixed number of observations in the demarcated region is obtained. If rejection is not indicated even at that stage, acceptance is recommended. Different large sample procedures based on this approach are formulated and examined.

Designs Robust Against Aberrations

1993 ◽  
Vol 43 (1-2) ◽  
pp. 95-108 ◽  
Author(s):  
N. K. Mandal ◽  
K. R. Shah
Keyword(s):  
Sufficient Conditions ◽  
Subject Classification ◽  
Alternative Formulation ◽  
Block Designs ◽  
Ams Subject Classification ◽  
Secondary 62K05

In this paper, we obtain sufficient conditions for a design to be robust against aberrations in the sense of Box and Draper. Block designs, row-column designs and fractional designs are considered here. An alternative formulation of robustness is also presented. AMS Subject Classification: Primary 62K99; Secondary 62K05.

scholarly journals Success run statistics defined on an urn model

2007 ◽  
Vol 39 (04) ◽  
pp. 991-1019 ◽  
Author(s):  
Frosso S. Makri ◽  
Andreas N. Philippou ◽  
Zaharias M. Psillakis
Keyword(s):  
Joint Probability ◽  
Nonparametric Tests ◽  
Distribution Functions ◽  
Binary Sequences ◽  
Binomial Coefficients ◽  
Joint Probability Distribution ◽  
Urn Model ◽  
Success Runs ◽  
Mean Values ◽  
Success Run

Statistics denoting the numbers of success runs of length exactly equal and at least equal to a fixed length, as well as the sum of the lengths of success runs of length greater than or equal to a specific length, are considered. They are defined on both linearly and circularly ordered binary sequences, derived according to the Pólya-Eggenberger urn model. A waiting time associated with the sum of lengths statistic in linear sequences is also examined. Exact marginal and joint probability distribution functions are obtained in terms of binomial coefficients by a simple unified combinatorial approach. Mean values are also derived in closed form. Computationally tractable formulae for conditional distributions, given the number of successes in the sequence, useful in nonparametric tests of randomness, are provided. The distribution of the length of the longest success run and the reliability of certain consecutive systems are deduced using specific probabilities of the studied statistics. Numerical examples are given to illustrate the theoretical results.

Mass transportation problems with capacity constraints

1999 ◽  
Vol 36 (2) ◽  
pp. 433-445 ◽  
Author(s):  
S. T. Rachev ◽  
I. Olkin
Keyword(s):  
Joint Distribution ◽  
Bivariate Distribution ◽  
Capacity Constraints ◽  
Distribution Functions ◽  
Mass Transportation ◽  
Marginal Distributions ◽  
Transportation Problems ◽  
The Family ◽  
Additional Capacity ◽  
Additional Constraints

We exhibit solutions of Monge–Kantorovich mass transportation problems with constraints on the support of the feasible transportation plans and additional capacity restrictions. The Hoeffding–Fréchet inequalities are extended for bivariate distribution functions having fixed marginal distributions and satisfying additional constraints. Sharp bounds for different probabilistic functionals (e.g. Lp-distances, covariances, etc.) are given when the family of joint distribution functions has prescribed marginal distributions, satisfies restrictions on the support, and is bounded from above, or below, by other distributions.

scholarly journals Two Higher Order Iterative Methods for Solving Nonlinear Equations

2018 ◽  
Vol 14 (1) ◽  
pp. 179-187
Author(s):  
Jivandhar Jnawali ◽  
Chet Raj Bhatta
Keyword(s):  
Iterative Methods ◽  
Nonlinear Equations ◽  
Order Of Convergence ◽  
Higher Order ◽  
Secant Method ◽  
Subject Classification ◽  
Numerical Examples ◽  
Ams Subject Classification

 The main purpose of this paper is to derive two higher order iterative methods for solving nonlinear equations as variants of Mir, Ayub and Rafiq method. These methods are free from higher order derivatives. We obtain these methods by amalgamating Mir, Ayub and Rafiq method with standard secant method and modified secant method given by Amat and Busquier. The order of convergence of new variants are four and six. Also, numerical examples are given to compare the performance of newly introduced methods with the similar existing methods. 2010 AMS Subject Classification: 65H05 Journal of the Institute of Engineering, 2018, 14(1): 179-187

scholarly journals Reinforcement Number of a Graph with respect to Half-Domination

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
G. Muhiuddin ◽  
N. Sridharan ◽  
D. Al-Kadi ◽  
S. Amutha ◽  
M. E. Elnair
Keyword(s):  
Upper Bounds ◽  
Subject Classification ◽  
Ams Subject Classification

In this paper, we introduce the concept of reinforcement number with respect to half-domination and initiate a study on this parameter. Furthermore, we obtain various upper bounds for this parameter. AMS subject classification: 05C38, 05C40, 05C69.

scholarly journals AMS subject classification:30C45 Meromorphically p-valent functions defined by integral operator involving ȴ-Function in new subclasses

2020 ◽  
Vol 25 (3) ◽  
Author(s):  
Ahmed Khalaf Radhi ◽  
Thamer Khalil Al-Khafaji
Keyword(s):  
Integral Operator ◽  
Convex Set ◽  
Subject Classification ◽  
Partial Sums ◽  
Coefficient Inequality ◽  
Ams Subject Classification ◽  
Distortion Bounds

Some relations in this paper we using  in  new subclass of meromorphically p-valent functions TK( ) defined by integral operator involving  -function  We derived some properties, like, coefficient inequality  , growth and distortion bounds by theorems (2) and (3), Partial sums, convex set, radii of starlikeness and radii  convexity.

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