Constructing median-unbiased estimators in one-parameter families of distributions via stochastic ordering
نویسندگان
چکیده
منابع مشابه
Hessian Stochastic Ordering in the Family of multivariate Generalized Hyperbolic Distributions and its Applications
In this paper, random vectors following the multivariate generalized hyperbolic (GH) distribution are compared using the hessian stochastic order. This family includes the classes of symmetric and asymmetric distributions by which different behaviors of kurtosis in skewed and heavy tail data can be captured. By considering some closed convex cones and their duals, we derive some necessary and s...
متن کاملStochastic ordering of classical discrete distributions
For several pairs (P,Q) of classical distributions on N0, we show that their stochastic ordering P ≤st Q can be characterized by their extreme tail ordering equivalent to P ({k∗})/Q({k∗}) ≤ 1 ≤ limk→k∗ P ({k})/Q({k}), with k∗ and k∗ denoting the minimum and the supremum of the support of P + Q, and with the limit to be read as P ({k∗})/Q({k∗}) for k∗ finite. This includes in particular all pair...
متن کاملSmall Parameter Behavior of Families of Distributions
For each t > 0 let Yt be a positive random variable with distribution Ft and Laplace Stieltjes transform (LST) ψt. In [1] it was shown that as t → 0, Y −t t converges in distribution to some Y with distribution F as t → 0 if and only if ψt(u) → 1 − F (u) for all continuity points u of F . The applicability of this result was demonstrated for numerous examples, all in which the limiting distribu...
متن کاملParameter estimation of ODE’s via nonparametric estimators
Ordinary differential equations (ODE’s) are widespread models in physics, chemistry and biology. In particular, this mathematical formalism is used for describing the sets of interactions and the evolution of complex systems and it might consist of high-dimensional sets of coupled nonlinear differential equations. In this setting, we propose a general method for estimating the parameters indexi...
متن کاملUnbiased Estimation of Parameter Sensitivities for Stochastic Chemical Reaction Networks
Estimation of parameter sensitivities for stochastic chemical reaction networks is an important and challenging problem. Sensitivity values are important in the analysis, modeling and design of chemical networks. They help in understanding the robustness properties of the system and also in identifying the key reactions for a given outcome. In a discrete setting, most of the methods that exist ...
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: Applicationes Mathematicae
سال: 2003
ISSN: 1233-7234,1730-6280
DOI: 10.4064/am30-3-1