Probability and Statistical Inference. Robert Bartoszynski
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Название: Probability and Statistical Inference

Автор: Robert Bartoszynski

Издательство: John Wiley & Sons Limited

Жанр: Математика

Серия:

isbn: 9781119243823

isbn:

СКАЧАТЬ for all images). However, if images, then images does not belong to any images with even images. Thus, images, and the sequence images does not converge.

      Infinite operations on events play a very important role in the development of the theory, especially in determining limiting probabilities.

      The definitions below will prepare the ground for the considerations in the following chapters. In Chapter 2, we will introduce probability as a number assigned to an event. Formally, we will be considering numerical functions defined on events, that is, on subsets of the sample space images. As long as images is finite or countably infinite, we can take the class of all subsets of images as the domain of definition of probability. In case of infinite but not countable images (e.g., where images is an interval, the real line, or a plane), it may not be possible to define probability on the class of all subsets of images. Although the explanation lies beyond the scope of this book, we will show how the difficulties can be avoided by suitable restriction of the class of subsets of images that are taken as events. We begin with the concept of closure under some operation.

      Definition 1.4.1 We say that the class images of subsets of images is closed under a given operation if the sets resulting from performing this operation on elements of images are also elements of images. images

      Complementation images, finite union images, infinite union images, limits of sequences images, are few examples of such operations.

      Example 1.18

      Let images and let images consist of all subsets of images that are finite. images is closed under finite unions and all intersections, finite or not. Indeed, if images are finite sets, then images is also finite. Similarly, if images are finite, then images, and hence images is also finite. However, images is not closed under complementation: if images is finite (images), then images is not finite, and hence images. On the other hand, if images is the class of all subsets of images that contain some fixed element, say 0, then images is closed under all intersections and unions, but it is not closed under complementation.

      The following concepts have an important role in the theory of probability.