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- Smoothness_(probability_theory) abstract "In probability theory and statistics, smoothness of a density function is a measure which determines how many times the density function can be differentiated, or equivalently the limiting behavior of distribution’s characteristic function.Formally, we call the distribution of a random variable X ordinary smooth of order β if its characteristic function satisfies for some positive constants d0, d1, β. The examples of such distributions are gamma, exponential, uniform, etc.The distribution is called supersmooth of order β if its characteristic function satisfies for some positive constants d0, d1, β, γ and constants β0, β1. Such supersmooth distributions have derivatives of all orders. Examples: normal, Cauchy, mixture normal.".
- Smoothness_(probability_theory) wikiPageID "24140640".
- Smoothness_(probability_theory) wikiPageRevisionID "449735073".
- Smoothness_(probability_theory) hasPhotoCollection Smoothness_(probability_theory).
- Smoothness_(probability_theory) subject Category:Theory_of_probability_distributions.
- Smoothness_(probability_theory) comment "In probability theory and statistics, smoothness of a density function is a measure which determines how many times the density function can be differentiated, or equivalently the limiting behavior of distribution’s characteristic function.Formally, we call the distribution of a random variable X ordinary smooth of order β if its characteristic function satisfies for some positive constants d0, d1, β.".
- Smoothness_(probability_theory) label "Smoothness (probability theory)".
- Smoothness_(probability_theory) sameAs m.07khfwk.
- Smoothness_(probability_theory) sameAs Q7546461.
- Smoothness_(probability_theory) sameAs Q7546461.
- Smoothness_(probability_theory) wasDerivedFrom Smoothness_(probability_theory)?oldid=449735073.
- Smoothness_(probability_theory) isPrimaryTopicOf Smoothness_(probability_theory).