A simple estimator of the bivariate distribution function for censored gap times

2008 ◽  
Vol 78 (15) ◽  
pp. 2440-2445 ◽  
Author(s):  
Jacobo de Uña-Álvarez ◽  
Luis F. Meira-Machado
Keyword(s):  
Distribution Function ◽  
Bivariate Distribution ◽  
Gap Times

AN EOQ MODEL WITH CONTROLLABLE SELLING RATE

2008 ◽  
Vol 25 (02) ◽  
pp. 151-167 ◽  
Author(s):  
HORNG-JINH CHANG ◽  
PO-YU CHEN
Keyword(s):  
Distribution Function ◽  
Transaction Cost ◽  
Optimal Solution ◽  
Bivariate Distribution ◽  
Inventory Level ◽  
Selling Price ◽  
Eoq Model ◽  
Concrete Form ◽  
Demand Rate ◽  
Classical Economic

According to the marketing principle, a decision maker may control demand rate through selling price and the unit facility cost of promoting transaction. In fact, the upper bound of willing-to-pay price and the transaction cost probably depend upon the subjective judgment of individual consumer in purchasing merchandise. This study therefore attempts to construct a bivariate distribution function to simultaneously incorporate the willing-to-pay price and the transaction cost into the classical economic order quantity (EOQ) model. Through the manipulation of the constructed bivariate distribution function, the demand function faced by the supplier can be expressed as a concrete form. The proposed mathematical model mainly concerns how to determine the initial inventory level for each business cycle, so that the profit per unit time is maximized by means of the selling price and the unit-transaction cost to control the selling rate. Furthermore, the sensitivity analysis of optimal solution is performed and the implication of this extended inventory model is also discussed.

scholarly journals Clayton Copula as an Alternative Perspective of Multi-Reaction Model

2018 ◽  
Vol 22 (1) ◽  
pp. 83-106 ◽  
Author(s):  
Alok Dhaundiyal ◽  
Suraj B. Singh ◽  
Muammel M. Hanon ◽  
Norbert Schrempf
Keyword(s):  
Activation Energy ◽  
Distribution Function ◽  
Numerical Solutions ◽  
Analytical Data ◽  
Initial Distribution ◽  
Reaction Model ◽  
Bivariate Distribution ◽  
Clayton Copula ◽  
Scale Parameters ◽  
Temperature Ramp

Abstract This study proposes to assess the effect of some relevant parameters of biomass pyrolysis on the numerical solutions of nthorder distributed activation energy model (DAEM) or multi reaction model (MRM). The two-step process mechanisms of pyrolysis is described by replacing the initial distribution function of f (E) with the Clayton copula. The upper limit (E∞) of ‘dE’ integral, activation energy (A), heating rate (m), and the shape and scale parameters of bivariate distribution function. Temperature ramp rate is assumed to vary linearly with time. Thermo-analytical data is obtained with the help of thermogravimetric (TG) analysis. Asymptotic technique is adopted to approximate double exponential and bivariate distribution function f (E1, E2), where E1and E2are the activation energies for bivariate scheme.

Distance methods applied to a semi-deterministic clustering process

1975 ◽  
Vol 7 (3) ◽  
pp. 450-451
Author(s):  
Peter Diggle
Keyword(s):  
Distribution Function ◽  
Spatial Patterns ◽  
Unit Area ◽  
Bivariate Distribution ◽  
Random Numbers ◽  
Distance Methods ◽  
The Mean ◽  
Image Position

Aggregated spatial patterns may be generated by a clustering process (see, for example, Bartlett (1964)) in which ‘parent’ events are distributed completely at random, and produce, independently, random numbers of ‘offspring’ according to some distribution Pn; the position of each offspring relative to its parent is governed, independently, by a given bivariate distribution. Parents and offspring are assumed indistinguishable. For such a process, Bartlett (1974) shows that the distribution function F of the distance, X say, from a randomly selected point to the nearest event is given by where ρ denotes the mean number of parents per unit area, A is the circle with centre the origin and radius x, and E(ds) denotes the event ‘no offspring in A from parent in ds’.

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