2,937 research outputs found
Stochastically Perturbed Chains of Variable Memory
In this paper, we study inference for chains of variable order under two
distinct contamination regimes. Consider we have a chain of variable memory on
a finite alphabet containing zero. At each instant of time an independent coin
is flipped and if it turns head a contamination occurs. In the first regime a
zero is read independent of the value of the chain. In the second regime, the
value of another chain of variable memory is observed instead of the original
one. Our results state that the difference between the transition probabilities
of the original process and the corresponding ones of the contaminated process
may be bounded above uniformly. Moreover, if the contamination probability is
small enough, using a version of the Context algorithm we are able to recover
the context tree of the original process through a contaminated sample
Perfect simulation of a coupling achieving the -distance between ordered pairs of binary chains of infinite order
We explicitly construct a coupling attaining Ornstein's -distance
between ordered pairs of binary chains of infinite order. Our main tool is a
representation of the transition probabilities of the coupled bivariate chain
of infinite order as a countable mixture of Markov transition probabilities of
increasing order. Under suitable conditions on the loss of memory of the
chains, this representation implies that the coupled chain can be represented
as a concatenation of iid sequence of bivariate finite random strings of
symbols. The perfect simulation algorithm is based on the fact that we can
identify the first regeneration point to the left of the origin almost surely.Comment: Typos corrected. The final publication is available at
http://www.springerlink.co
Perfect simulation for interacting point processes, loss networks and Ising models
We present a perfect simulation algorithm for measures that are absolutely
continuous with respect to some Poisson process and can be obtained as
invariant measures of birth-and-death processes. Examples include area- and
perimeter-interacting point processes (with stochastic grains), invariant
measures of loss networks, and the Ising contour and random cluster models. The
algorithm does not involve couplings of the process with different initial
conditions and it is not tied up to monotonicity requirements. Furthermore, it
directly provides perfect samples of finite windows of the infinite-volume
measure, subjected to time and space ``user-impatience bias''. The algorithm is
based on a two-step procedure: (i) a perfect-simulation scheme for a (finite
and random) relevant portion of a (space-time) marked Poisson processes (free
birth-and-death process, free loss networks), and (ii) a ``cleaning'' algorithm
that trims out this process according to the interaction rules of the target
process. The first step involves the perfect generation of ``ancestors'' of a
given object, that is of predecessors that may have an influence on the
birth-rate under the target process. The second step, and hence the whole
procedure, is feasible if these ``ancestors'' form a finite set with
probability one. We present a sufficiency criteria for this condition, based on
the absence of infinite clusters for an associated (backwards) oriented
percolation model.Comment: Revised version after referee of SPA: 39 page
The Use of the Agency Healthcare Research and Quality Patient Safety Indicator 11 Toolkit to Decrease Postoperative Respiratory Failure
Postoperative respiratory failure incidents can lead to adverse outcomes, including prolonged hospitalizations, increased admissions to intensive care units, and the risk of complications such as ventilator-associated pneumonia, sepsis, and mortality. This project aimed to assess the effectiveness of implementing the Agency for Healthcare Research and Quality Patient Safety Indicator 11 toolkit intervention for noninvasive positive-pressure ventilation in reducing postoperative respiratory failure rates compared to traditional practices. Adopting evidence- based toolkits, such as those provided by the Agency for Healthcare Research and Quality, aids healthcare organizations in enhancing the quality of patient care. The quality improvement project employed a quasi-experimental design, comparing two groups: one receiving the toolkit intervention and another adhering to traditional practices. Postoperative respiratory failure incidences in the year prior within the same timeframe were compared to the outcomes of the quality improvement project. These positive outcomes underscore the importance of implementing the Agency for Healthcare Research and Quality Patient Safety Indicator 11 toolkit intervention as a quality improvement initiative in healthcare organizations. This intervention has the potential to substantially reduce postoperative respiratory failure rates and associated complications
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