One inherent weakness of traditional reliability theory (see eqr 340) is that the system and the components are always described just as functioning or failed. The first attempts to replace this by a theory for multistate systems of multistate components were made in the late 1970s. By the mid 1980s the basic theory in this area was established. The objective of this article is to introduce con...

In many chronic diseases, the patient's health status is followed up by quantitative markers. The evolution is often characterized by a 2-phase degradation process, that is, a normal phase followed by a pathological degradation phase preceding the disease diagnosis. We propose a joint multistate model with latent state for the joint modeling of repeated measures of a quantitative marker, time-t...

Time-to-event and similar analyses can be problematic if the event of interest is operationally defined by some condition being true for a prolonged period of time. A particular example of this, remission in psoriatic arthritis, is considered in detail for illustration. A 3-state model is proposed for characterizing the transition rates into and out of remission. Remission is linked to an initi...

The classical hard core model from statistical physics, with activity λ > 0 and capacity C = 1, on a graph G, concerns a probability measure on the set I(G) of independent sets of G, with the measure of each independent set I ∈ I(G) being proportional to λ|I|. Ramanan et al. proposed a generalization of the hard core model as an idealized model of multicasting in communication networks. In this...

As cancer patient survival improves, late effects from treatment are becoming the next clinical challenge. Chemotherapy and radiotherapy, for example, potentially increase risk of both morbidity mortality second malignancies cardiovascular disease. To provide clinically relevant population-level measures effects, it is importance to (1) simultaneously estimate risks mortality, (2) partition the...

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state m...