A daily stochastic spatiotemporal precipitation generator that yields precipitation realizations that are quantitatively consistent is described. The methodology relies on a latent Gaussian field that drives both the occurrence and intensity of the precipitation process. For the precipitation intensity, the marginal distributions, which are space and time dependent, are described by a composite model of a gamma distribution for observations below some threshold with a generalized Pareto distribution modeling the excesses above the threshold. Model parameters are estimated from data and extrapolated to locations and times with no direct observations using linear regression of position covariates. One advantage of such a model is that stochastic generator parameters are readily available at any location and time of the year inside the stationarity regions. The methodology is illustrated for a network of 12 locations in Sweden. Performance of the model is judged through its ability to accurately reproduce a series of spatial dependence measures and weather indices.
In this paper, we propose a new method for modelling precipitation in Sweden. We consider a chain dependent stochastic model that consists of a component that models the probability of occurrence of precipitation at a weather station and a component that models the amount of precipitation at the station when precipitation does occur. For the first component, we show that for most of the weather stations in Sweden a Markov chain of an order higher than one is required. For the second component, which is a Gaussian process with transformed marginals, we use a composite of the empirical distribution of the amount of precipitation below a given threshold and the generalized Pareto distribution for the excesses in the amount of precipitation above the given threshold. The derived models are then used to compute different weather indices. The distribution of the modelled indices and the empirical ones show good agreement, which supports the choice of the model.
A study of a population sample of women in Göteborg aged 38--60 years was carried out in 1968--1969. This population sample has been re-studied during the years 1974--1975. Altogether 1302 women participated in this second study, which means 89.1% of those studied in 1968--1969 and 80.3% of those initially sampled. Twenty-six women had died during the interval between the two studies, more than half of them from neoplastic disease. Information is given about those who had moved or were inaccessible at the time of the second study or who refused to participate. The performance of the examination is described and research projects are outlined.
We set up a game theoretic framework to analyze a wide range of situations from team sports. A fundamental idea is the concept of potential; the probability of the offense scoring the next goal minus the probability that the next goal is made by the defense. We develop categorical as well as continuous models, and obtain optimal strategies for both offense and defense. A main result is that the optimal defensive strategy is to minimize the maximum potential of all offensive strategies.
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