Parameter shift in linear regression.

The mathematical framework for statistical decision theory is provided by the theory of probability which in turn has its foundations in the theory of measure and integration. In constructing a probability model for an experiment, the first step is a consideration of what are the possible outcomes o...

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Bibliographic Details
Main Author:	Tracey, Sister. St. G.
Other Authors:	Guttman, I. (Supervisor)
Format:	Others
Language:	en
Published:	McGill University 1963
Subjects:	Mathematics.
Online Access:	http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=115293

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spelling	ndltd-LACETR-oai-collectionscanada.gc.ca-QMM.1152932014-02-13T04:10:01ZParameter shift in linear regression.Tracey, Sister. St. G.Mathematics.The mathematical framework for statistical decision theory is provided by the theory of probability which in turn has its foundations in the theory of measure and integration. In constructing a probability model for an experiment, the first step is a consideration of what are the possible outcomes of the experiment. We assume that all possibilities for the outcomes can be foreseen, and we refer to this collection of outcomes as the sample space H. An arbitrary outcome or point of this space is designated by x. The events to be studied are aggregates of such outcomes, they are represented by subsets of H which belong to the σ-algebra A.McGill UniversityGuttman, I. (Supervisor)1963Electronic Thesis or Dissertationapplication/pdfenalephsysno: NNNNNNNNNTheses scanned by McGill Library.All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.Master of Science. (Department of Mathematics.) http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=115293
collection	NDLTD
language	en
format	Others
sources	NDLTD
topic	Mathematics.
spellingShingle	Mathematics. Tracey, Sister. St. G. Parameter shift in linear regression.
description	The mathematical framework for statistical decision theory is provided by the theory of probability which in turn has its foundations in the theory of measure and integration. In constructing a probability model for an experiment, the first step is a consideration of what are the possible outcomes of the experiment. We assume that all possibilities for the outcomes can be foreseen, and we refer to this collection of outcomes as the sample space H. An arbitrary outcome or point of this space is designated by x. The events to be studied are aggregates of such outcomes, they are represented by subsets of H which belong to the σ-algebra A.
author2	Guttman, I. (Supervisor)
author_facet	Guttman, I. (Supervisor) Tracey, Sister. St. G.
author	Tracey, Sister. St. G.
author_sort	Tracey, Sister. St. G.
title	Parameter shift in linear regression.
title_short	Parameter shift in linear regression.
title_full	Parameter shift in linear regression.
title_fullStr	Parameter shift in linear regression.
title_full_unstemmed	Parameter shift in linear regression.
title_sort	parameter shift in linear regression.
publisher	McGill University
publishDate	1963
url	http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=115293
work_keys_str_mv	AT traceysisterstg parametershiftinlinearregression
_version_	1716646635500470272

Parameter shift in linear regression.

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