An algorithm for solving a constrained least squares problem for estimating the effects of an unknown monotonically intervening factor

Wadhwa, Shalini

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dc.contributor.author	Wadhwa, Shalini
dc.contributor.other	Youngstown State University, degree granting institution.
dc.contributor.other	Youngstown State University. Department of Mathematics.
dc.date.accessioned	2021-09-21T15:47:23Z
dc.date.available	2021-09-21T15:47:23Z
dc.date.issued	1991
dc.identifier.other	B22676004
dc.identifier.other	1198612662
dc.identifier.uri	https://jupiter.ysu.edu:443/record=b2267600
dc.identifier.uri	http://hdl.handle.net/1989/16589
dc.description	50 leaves : illustrations ; 29 cm M.S. Youngstown State University 1991. Includes bibliographical references (leaves 48-49).	en_US
dc.description.abstract	The conventional least squares method cannot estimate any hidden causal factor which is assumed to shift the regression hyperplane monotonically upwards (downwards). A constrained least squares problem has been formulated by S. Thore to model this phenomenon. A compact and efficient algorithm is developed and presented to solve this constrained problem. Computational results are presented which illustrate the effectiveness of this algorithm. The new method is then used to estimate the price elasticity of cigarettes and the monotonic shifts of the demand curve. A causal factor is found which may reflect the awareness among the general public of the harmful effects of smoking.	en_US
dc.description.sponsorship	Youngstown State University. Department of Mathematics.	en_US
dc.language.iso	en_US	en_US
dc.publisher	[Youngstown, Ohio] : Youngstown State University, 1991.	en_US
dc.relation.ispartofseries	Master's Theses;no. 0436
dc.subject	Least squares.	en_US
dc.title	An algorithm for solving a constrained least squares problem for estimating the effects of an unknown monotonically intervening factor	en_US
dc.type	Thesis	en_US

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