Joint Measures and Cross-covariance Operators Jon·it I"leasures and Cross-covariance Operators Joint L"leasljres and Cross-covariance Operators*

نویسنده

  • Charles R. Baker
چکیده

Let HI (resp., HZ) be a real and separable Hilbert space with Borel a-field f 1 (resp., f 2), and let (HIXH Z ' f 1 x f 2) be the product measurable space generated by the measurable rectangles. This paper develops relations between probability measures on (HIXH Z ' f 1 x f 2), i.e., joint measures, and the projections of such measures on (HI' f 1) and (HZ' f 2). In particular, the class of all joint Gaussian measures having two specified Gaussian measures as projections is characterized, and conditions are obtained for two joint Gaussian measures to be mutually absolutely continuous. The cross-covariance operator of a joint measure plays a major role in these results, and these operators are characterized.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

JOINT MEASURES AND CROSS - COVARIANCE OPERATORS ( l )

Let H. (resp., H ) be a real and separable Hubert space with Borel O'field T (resp., rj, and let (H. X //-, T, X T.) be the product measurable space generated by the measurable rectangles. This paper develops relations between probability measures on (H. x H , V x T.), i.e., joint measures, and the projections of such measures on (H., T.) and (H , Y ). In particular, the class of all joint Gaus...

متن کامل

Matérn-based nonstationary cross-covariance models for global processes

Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible crosscovariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-...

متن کامل

Kernel Measures of Conditional Dependence

We propose a new measure of conditional dependence of random variables, based on normalized cross-covariance operators on reproducing kernel Hilbert spaces. Unlike previous kernel dependence measures, the proposed criterion does not depend on the choice of kernel in the limit of infinite data, for a wide class of kernels. At the same time, it has a straightforward empirical estimate with good c...

متن کامل

Learning causality by identifying common effects with kernel-based dependence measures

We describe a method for causal inference that measures the strength of statistical dependence by the Hilbert-Schmidt norm of kernelbased conditional cross-covariance operators. We consider the increase of the dependence of two variables X and Y by conditioning on a third variable Z as a hint for Z being a common effect of X and Y . Based on this assumption, we collect “votes” for hypothetical ...

متن کامل

On convergence of sample and population Hilbertian functional principal components

In this article we consider the sequences of sample and population covariance operators for a sequence of arrays of Hilbertian random elements. Then under the assumptions that sequences of the covariance operators norm are uniformly bounded and the sequences of the principal component scores are uniformly sumable, we prove that the convergence of the sequences of covariance operators would impl...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1971