Kernel canonical correlation analysis (CCA) is a nonlinear extension of CCA, which aims at extracting information shared by two random variables. In this paper, a new notion of conditional kernel CCA is introduced. Conditional kernel CCA aims at analyzing the effect of variable Z to the dependence between X and Y . Rates of convergence of an empirical normalized conditional cross-covariance ope...

in general, energy prices, such as those of crude oil, are affected by deterministic events such as seasonal changes as well as non-deterministic events such as geopolitical events. it is the non-deterministic events which cause the prices to vary randomly and makes price prediction a difficult task. one could argue that these random changes act like noise which effects the deterministic variat...

OBJECTIVE To determine the effect of inequalities in income within a state on self rated health status while controlling for individual characteristics such as socioeconomic status. DESIGN Cross sectional multilevel study. Data were collected on income distribution in each of the 50 states in the United States. The Gini coefficient was used to measure statewide inequalities in income. Random ...

Two conditional expectations in unbounded operator algebras (O∗-algebras) are discussed. One is a vector conditional expectation defined by a linear map of an O∗-algebra into the Hilbert space on which the O∗-algebra acts. This has the usual properties of conditional expectations. This was defined by Gudder and Hudson. Another is an unbounded conditional expectation which is a positive linear m...

Given a longitudinal network observed at time points t1 < · · · < tT , tie changes that happen in the interval (th, th+1) typically depend on the networks at t1, . . . , th. In this article we deal with the question whether changes within one interval mutually depend on each other or whether they are conditionally independent, given the previously observed networks. Answering this question for ...

Conditional narrowing is underlying computational mechanism of most functional-logic programming languages. It is important to ensure completeness of conditional narrowing for conditional term rewriting systems without assumption of termination because termination is a too severe restriction for programming languages. In this paper we show completeness of conditional narrowing for a kind of ort...

Received Apr 11, 2017 Revised May 5, 2017 Accepted May 24, 2017 Conditional functional dependencies (CFDs) have been used to improve the quality of data, including detecting and repairing data inconsistencies. Approximation measures have significant importance for data dependencies in data mining. To adapt to exceptions in real data, the measures are used to relax the strictness of CFDs for mor...

As the paper explains, it is crucial to epistemology in general and to the theory of causation in particular to investigate the properties of conditional independence as completely as possible. The paper summarizes the most important results concerning conditional independence with respect to two important representations of epistemic states, namely (strictly positive) probability measures and ...