A sharp inequality for the $p$-center of gravity of a random variable

AbstractA Logistic-Normal random variable (Y) is obtained from a Normal random variable (X) by the relation Y = (ex)/(1 + ex). In Monte-Carlo analysis of decision trees, Logistic-Normal random variates may be used to model the branching probabilities. In some cases, the probabilities to be modeled may not be independent, and a method for generating correlated Logistic-Normal random variates would be useful. A technique for generating correlated Normal random variates has been previously described. Using Taylor Series approximations and the algebraic definitions of variance and covariance, we describe methods for estimating the means, variances, and covariances of Normal random variates which, after translation using the above formula, will result in Logistic-Normal random variates having approximately the desired means, variances, and covariances. Multiple simulations of the method using the Mathematica computer algebra system show satisfactory agreement with the theoretical results.

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Classification of Acceleration Waveforms during Walking by Wavelet Transform

Methods of Information in Medicine ◽

10.1055/s-0038-1636855 ◽

1997 ◽

Vol 36 (04/05) ◽

pp. 356-359 ◽

Cited By ~ 27

Author(s):

M. Sekine ◽

M. Ogawa ◽

T. Togawa ◽

Y. Fukui ◽

T. Tamura

Keyword(s):

Wavelet Transform ◽

Wavelet Analysis ◽

Center Of Gravity ◽

Dynamic Responses ◽

Sequential Data ◽

Acceleration Signal ◽

Continuous Dynamic

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.

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OPTIMIZATION OF MARKOV SYSTEMS OF QUEUEING WITH WAITING TIME IN THE MATLAB SYSTEM

VESTNIK OF ASTRAKHAN STATE TECHNICAL UNIVERSITY SERIES MANAGEMENT COMPUTER SCIENCE AND INFORMATICS ◽

10.24143/2072-9502-2017-2-39-47 ◽

2017 ◽

pp. 39-47

Author(s):

Viktor Afonin ◽

Vladimir Valer'evich Nikulin

Keyword(s):

Queueing System ◽

Queueing Systems ◽

Random Variable ◽

Model Systems ◽

Queuing Systems ◽

Input Flow ◽

Continuous Random Variable ◽

Input Stream ◽

Time Intervals ◽

Markov Systems

The article focuses on attempt to optimize two well-known Markov systems of queueing: a multichannel queueing system with finite storage, and a multichannel queueing system with limited queue time. In the Markov queuing systems, the intensity of the input stream of requests (requirements, calls, customers, demands) is subject to the Poisson law of the probability distribution of the number of applications in the stream; the intensity of service, as well as the intensity of leaving the application queue is subject to exponential distribution. In a Poisson flow, the time intervals between requirements are subject to the exponential law of a continuous random variable. In the context of Markov queueing systems, there have been obtained significant results, which are expressed in the form of analytical dependencies. These dependencies are used for setting up and numerical solution of the problem stated. The probability of failure in service is taken as a task function; it should be minimized and depends on the intensity of input flow of requests, on the intensity of service, and on the intensity of requests leaving the queue. This, in turn, allows to calculate the maximum relative throughput of a given queuing system. The mentioned algorithm was realized in MATLAB system. The results obtained in the form of descriptive algorithms can be used for testing queueing model systems during peak (unchanged) loads.

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Some Statistical Properties of a Damage Random Variable in Invasive Species Management

Studies in Regional Science ◽

10.2457/srs.42.189 ◽

2012 ◽

Vol 42 (1) ◽

pp. 189-195

Author(s):

Amitrajeet A.BATABYAL

Keyword(s):

Invasive Species ◽

Random Variable ◽

Statistical Properties ◽

Invasive Species Management ◽

Species Management

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Determination of Optimal Reserve between Two Machines in Series with the Repair Time has Change of Distribution after the Truncation Point

GIS Business ◽

10.26643/gis.v14i6.14581 ◽

2019 ◽

Vol 14 (6) ◽

pp. 577-585

Author(s):

T. Vivekanandan ◽

S. Sachithanantham

Keyword(s):

Real Life ◽

Random Variable ◽

Repair Time ◽

Inventory Level ◽

Optimal Size ◽

Truncation Point ◽

In Series ◽

Optimal Reserve ◽

Optimal Inventory Level ◽

Two Machines

In inventory control, suitable models for various real life systems are constructed with the objective of determining the optimal inventory level. A new type of inventory model using the so-called change of distribution property is analyzed in this paper. There are two machines M1 and M2 in series and the output of M1 is the input of M2. Hence a reserve inventory between M1 and M2 is to be maintained. The method of obtaining the optimal size of reserve inventory, assuming cost of excess inventory, cost of shortage and when the rate of consumption of M2 is a constant, has already been attempted. In this paper, it is assumed that the repair time of M1 is a random variable and the distribution of the same undergoes a change of distribution after the truncation point X0 , which is taken to be a random variable. The optimal size of the reserve inventory is obtained under the above said assumption . Numerical illustrations are also provided.

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