Decreasing Failure Rate Property Research Articles

The DFR Property for Counting Processes Stopped at an Independent Random Time

In this paper we consider general counting processes stopped at a random timeT, independent of the process. Provided thatThas the decreasing failure rate (DFR) property, we present sufficient conditions on the arrival times so that the number of events occurring beforeTpreserves the DFR property ofT. In particular, when the interarrival times are independent, we consider applications concerning the DFR property of the stationary number of customers waiting in queue for specific queueing models.

The DFR Property for Counting Processes Stopped at an Independent Random Time

In this paper we consider general counting processes stopped at a random time T, independent of the process. Provided that T has the decreasing failure rate (DFR) property, we present sufficient conditions on the arrival times so that the number of events occurring before T preserves the DFR property of T. In particular, when the interarrival times are independent, we consider applications concerning the DFR property of the stationary number of customers waiting in queue for specific queueing models.

Concave Renewal Functions do not Imply DFR Interrenewal Times

Brown (1980), (1981) proved that the renewal function is concave if the interrenewal distribution is DFR (decreasing failure rate), and conjectured the converse. This note settles Brown's conjecture with a class of counterexamples. We also give a short proof of Shanthikumar's (1988) result that the DFR property is closed under geometric compounding.

Concave Renewal Functions do not Imply DFR Interrenewal Times

Brown (1980), (1981) proved that the renewal function is concave if the interrenewal distribution is DFR (decreasing failure rate), and conjectured the converse. This note settles Brown's conjecture with a class of counterexamples. We also give a short proof of Shanthikumar's (1988) result that the DFR property is closed under geometric compounding.

Ageing Characteristics of the Weibull Mixtures

It is well known that mixtures of decreasing failure rate (DFR) distributions have the DFR property. A similar result is, of course, not true for increasing failure rate (IFR) distributions. In a recent note, Gurland and Sethuraman (1994, Technometrks36(4): 416–418) presented two examples where mixtures of IFR distributions show DFR property. In this paper, we present a general approach to study the mixtures of distributions and show that the failure rates of the unconditional and conditional distributions cross at most at one point. Mixtures of Weibull distribution with a shape parameter greater than 1 are examined in detail. This also enables us to study the monotonic properties of the mean residual life function of the mixture. Some examples are provided to illustrate the results.

How Pooling Failure Data May Reverse Increasing Failure Rates

Abstract Although mixtures of decreasing failure rate (DFR) distributions are always DFR, some mixtures of increasing failure rate (IFR) distributions can also be ultimately DFR. In this article various types of discrete and continuous mixtures of IFR distributions are considered, and conditions are developed for such mixtures to be ultimately DFR. These conditions lead to an interesting result—that certain mixtures of IFR distributions, even those with very rapidly increasing failure rates (e.g., Weibull, truncated extreme), ultimately become DFR distributions. It is common practice to pool data from several different IFR distributions to enlarge sample size, for instance. The results of this article sound a warning that such pooling may actually reverse the IFR property of the individual samples to a DFR property.

DFR Property of First-Passage Times and its Preservation Under Geometric Compounding

It is shown that if a discrete-time Markov chain on the state space $\{0, 1,\ldots\}$ has a transition probability matrix $\mathbf{P}$ and a transition survival probability matrix $\mathbf{Q}$ which is totally positive of order two $(TP_2)$, where $Q(i, j) = \sum_{k\geq j}P(i, k)$, then the first-passage time from state 1 to state 0 has decreasing failure rate (DFR). This result is used to show that (i) the sum of a geometrically distributed number (i.e., geometric compound) of i.i.d. DFR random variables is DFR, and (ii) the number of customers served during a busy period in an M/G/1 queue with increasing failure-rate service times is DFR. Recent results of Szekli (1986) and the closure property of i.i.d. DFR random variables under geometric compounding are combined to show that the stationary waiting time in a GI/G/1 (M/G/1) queue with DFR (increasing mean residual life) service times is DFR. We also provide sufficient conditions on the inter-renewal times under which the renewal function is concave. These results shed some light on a conjecture of Brown (1981).

Approximations in Renewal Theory

A renewal process [N(t), t ≥ 0] with interarrival times Xi, for i ≥ 1 and renewal function m (t) is considered. Let Gn, λ denote the gamma distribution with parameters n and λ–that is, dGn, λ(x) = λε–λx(λx)n-1/(n – 1)In Section 1 we show how m(t) can be approximated by f m(s) dGn, n/t(s). In addition, we show that these approximations constitute an increasing sequence of lower bounds when the interarrival distribution has the decreasing failure rate property. In Section 2 we show how the integrated renewal function can be approximated in a similar fashion by a decreasing sequence of upper bounds. In Section 3 we consider the problem of approximating the residual life (also called excess life) and the renewal age distribution and their means, and in Section 4 we consider the distribution of N(t). Finally, in Section 5 we remark on the relationship between our approximations and the Feller technique for inverting a Laplace transform.

Theorems on log-convex disposition curves in drug and tracer kinetics

Conventionally, analysis of the dynamic behaviour of substances in the whole organism is based on the multiexponential paradigm (compartmental model). Alternatively the use of power functions has been proposed. In this paper a unified view is developed investigating the implications of observed log-convexity of disposition (clearance) curves. Using a non-compartmental approach it is proved that the disposition residence time distribution corresponding to a log-convex impulse response (blood concentration-time curve) belongs to the DFR (decreasing failure rate) class, implying that (1) the disposition curve has an exponential tail and (2) the relative dispersion of residence times is greater than or equal to one. This class of disposition curves includes multiexponential and power functions as special cases. In terms of the underlying biophysical principles the DFR property is discussed as a consequence of a dominant role of passive distribution processes of particles in the organism. The paper also deals with the corresponding properties of a recirculatory model using renewal theoretic concepts.