Criterion for unlimited growth of critical multidimensional stochastic models
نویسندگان
چکیده
منابع مشابه
Criterion of unlimited growth of critical multidimensional stochastic models
where {Fn, n ∈ N}, is the natural filtration associated to (Xn). We assume that X0 ∈ R d + and that random vectors ξn are such that for all n, Xn ∈ R d + almost surely. The Perron-Frobenius Theorem [10, pp. 3-4] states that M has a positive Perron root ρ. We call Xn “subcritical” if ρ < 1, “supercritical” if ρ > 1 and “critical” if ρ = 1. In the “subcritical” case, one has P(‖Xn‖ → ∞) = 0 becau...
متن کاملStochastic models for tumoral growth.
Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border and the surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor bor...
متن کاملStochastic Models of Growth∗
In these notes we describe the existing results on the effects of ‘volatility,’ both in technologies and policies, on the long-run growth rate. We start with a brief summary of the empirical research in this area, and we then describe some simple theoretical models that are useful in understanding the empirical results. We end with the description of some recent work based on the theoretical mo...
متن کاملDeviance Information Criterion for Comparing Stochastic Volatility Models
Bayesian methods have been ef cient in estimating parameters of stochastic volatility models for analyzing nancial time series. Recent advances made it possible to t stochastic volatility models of increasing complexity, including covariates, leverage effects, jump components, and heavy-tailed distributions.However, a formal model comparison via Bayes factors remains dif cult. The main ob...
متن کاملBayesian Optimum Design Criterion for Multi Models Discrimination
The problem of obtaining the optimum design, which is able to discriminate between several rival models has been considered in this paper. We give an optimality-criterion, using a Bayesian approach. This is an extension of the Bayesian KL-optimality to more than two models. A modification is made to deal with nested models. The proposed Bayesian optimality criterion is a weighted average, where...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advances in Applied Probability
سال: 2016
ISSN: 0001-8678,1475-6064
DOI: 10.1017/apr.2016.61