Download e-book for kindle: Applications of Discrete-time Markov Chains and Poisson by Eliane Regina Rodrigues, Jorge Alberto Achcar

By Eliane Regina Rodrigues, Jorge Alberto Achcar

ISBN-10: 1461446449

ISBN-13: 9781461446446

​In this short we think about a few stochastic versions which may be used to check difficulties comparable to environmental issues, particularly, air pollution.  The effect of publicity to air toxins on people's well-being is a really transparent and good documented topic. for that reason, it really is very important to procure how one can expect or clarify the behaviour of pollution usually. Depending on the kind of query that one is attracted to answering, there are numerous of how learning that problem. between them we may perhaps quote, research of the time sequence of the pollutants' measurements, analysis of the data received at once from the knowledge, for example, day-by-day, weekly or monthly averages and conventional deviations. otherwise to check the behaviour of toxins in most cases is through mathematical types. within the mathematical framework we could have for example deterministic or stochastic types. the kind of versions that we'll give some thought to during this short are the stochastic ones.​

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Extra resources for Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies (SpringerBriefs in Mathematics)

Example text

For instance, if we have T years of measurements, then for ni the number of exceedances of the threshold of interest in the ith year (i = 1, 2, . . , T ), the empirical mean is μ = (1/T ) ∑Ti=1 ni . 28 3 Poisson Models and Their Application to Ozone Data A similar calculation is given for the empirical variance (see for instance [65]). Then, using the relation between μ and σ 2 and α and β we solve the system of equations to obtain the hyperparameters α and β of the Gamma prior distribution. In [62] data from the Metropolitan Area of Mexico City were used.

2 Homogeneous Poisson Models When time homogeneous Poisson models are considered, what we are interested in is estimating the rate λ > 0. 2) to calculate the probability that a given environmental threshold is surpassed a number of times within a time interval of interest. Time homogeneous Poisson processes have been used to model several types of problems mainly those of determining the count of occurrences of events. Javits [45] considers that type of process to study the problem of counting the number of surpassings of an environmental threshold by the ozone concentration.

The hyperparameters were calculated using the empirical mean and variance obtained in the period 1997–1999 (inclusive) and 2000–2003 (inclusive). Hence, two sets of hyperparameters were use for each threshold considered. The reason for splitting the observational period to calculate the hyperparameters of the prior distributions is that in 1999 the last of a series of environmental measures aiming to reduce the level of ozone in Mexico City was implemented. Hence, changes in the behavior of that pollutant may be observed.

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Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies (SpringerBriefs in Mathematics) by Eliane Regina Rodrigues, Jorge Alberto Achcar

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