Applied Stochastic Models and Data Analysis

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010101

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010102

Guttman, Louis

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010103

Schader, Martin; Schmid, Friedrich

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010104

Computation of M. L. estimates for the parameters of a negative binomial distribution from grouped data is considered. For this problem the Scoring, Newton—Raphson and E‐M algorithm is derived. Using simulated data the performance of the algorithms is compared with respect to convergence, number of iterations and computing time. Finally an empirical example drawn from actuarial science is given.

Garcia, Hervé; Proth, Jean Marie

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010105

We consider a set of parts divided into subsets called part types, determined in such a way that the parts belonging to the same part type are manufactured using the same sequence of tasks (i.e. the same working process). We are looking for a partition of the set of part types into subsets called part families, and for a partition of the set of tasks into subsets called production subsystems defined as follows: (1) the number of part families and the number of production subsystems are equal, (2) one (one only one) production subsystem corresponds to each part family, (3) one (and only one) part family corresponds to each production subsystem, (4) the previous partitions minimize the number of tasks performed in a production subsystem different from that which corresponds to the part family containing the part involved. We give a fast algorithm which leads to a good solution depending on the initial set of part families. We also propose an algorithm to find a ‘good’ initial set of part families.

Parisot, Pierre

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010106

We studied a population of paraplegic patients in order to give prominence to a possible relationship between the topography of their spinal lesion and the occurrence of special articular diseases (P.O.A.).

Abikhalil, F.; Dupont, P.; Janssen, J.; van Ossel, P.

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010107

The purpose of this paper is to give a mathematical model to generalize the classical approach of compound interest and to overcome the time structure problem of the interest rates. We introduce a suitable stochastic process called the ‘gauge’ process such that its product with the value of any security is assumed to be a martingale in an appropriate probability space. The framework of this model gives a stochastic actualization formula for the pricing of general securities with options and includes Black and Schole's formula without using arbitrage arguments. Emphasis has been placed on numerical calculation.

Yamada, Shioeru; Osaki, Shunji

1985 Applied Stochastic Models and Data Analysis

doi: 10.1002/asm.3150010108

A general description of a discrete software reliability growth model, which adopts the number of test runs or the number of executed test cases as the unit of error detection period, is presented. Two classes of discrete software reliability growth models are proposed and discussed. These models can be described by non‐homogeneous Poisson processes, in which the random variable is denned as the number of errors detected by n test runs (n = 0, 1, 2,…). The application and comparison of these models to actual software error data are shown.