regression equations

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Seemingly Unrelated Regression Equations Models

Author : Virendera K. Srivastava
ISBN : 0824776100
Genre : Mathematics
File Size : 66. 31 MB
Format : PDF
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The seemingly unrelated regression equations model; The least squares estimator and its variants; Approximate destribution theory for feasible generalized least squares estimators; Exact finite-sample properties of feasible generalized least squares estimators; Iterative estimators; Shrinkage estimators; Autoregressive disturbances; Heteroscedastic disturbances; Constrained error covariance structures; Prior information; Some miscellaneous topics.

Development Of Regression Equations To Estimate Flow Durations And Low Flow Frequency Statistics In New Hampshire Streams

Author : Robert H. Flynn
ISBN : OSU:32435070235205
Genre : Electronic government information
File Size : 85. 1 MB
Format : PDF
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Regression Equations For Estimating Flood Flows For The 2 10 25 50 100 And 500 Year Recurrence Intervals In Connecticut

Author : Elizabeth A. Ahearn
ISBN : UCR:31210019469772
Genre : Electronic government information
File Size : 47. 92 MB
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Nationwide Summary Of U S Geological Survey Regional Regression Equations For Estimating Magnitude And Frequency Of Floods For Ungaged Sites 1993

Author :
ISBN : UIUC:30112059204674
Genre : Flood forecasting
File Size : 24. 62 MB
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Regression Equations For Estimating Concentrations Of Selected Water Quality Constituents For Selected Gaging Stations In The Red River Of The North Basin North Dakota Minnesota And South Dakota

Author :
ISBN : 9781428984516
Genre :
File Size : 64. 81 MB
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Multiple Regression Equations For Estimating Low Flows At Ungaged Stream Sites In Ohio

Author : G. F. Koltun
ISBN : UCR:31210024318303
Genre : Stream measurements
File Size : 64. 31 MB
Format : PDF
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Development Testing And Assessment Of Regression Equations For Experimental Forecasts Etc U S Geological Survey Water Resources Investigations Report 00 4153 2000

Author :
ISBN : PSU:000047055599
Genre :
File Size : 53. 70 MB
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Multiple Regression

Author : Leona S. Aiken
ISBN : 0761907122
Genre : Business & Economics
File Size : 38. 95 MB
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This successful book, now available in paperback, provides academics and researchers with a clear set of prescriptions for estimating, testing and probing interactions in regression models. Including the latest research in the area, such as Fuller's work on the corrected/constrained estimator, the book is appropriate for anyone who uses multiple regression to estimate models, or for those enrolled in courses on multivariate statistics.

Introduction To Nonparametric Regression

Author : K. Takezawa
ISBN : 9780471771449
Genre : Mathematics
File Size : 54. 15 MB
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An easy-to-grasp introduction to nonparametric regression This book's straightforward, step-by-step approach provides anexcellent introduction to the field for novices of nonparametricregression. Introduction to Nonparametric Regression clearlyexplains the basic concepts underlying nonparametric regression andfeatures: * Thorough explanations of various techniques, which avoid complexmathematics and excessive abstract theory to help readersintuitively grasp the value of nonparametric regressionmethods * Statistical techniques accompanied by clear numerical examplesthat further assist readers in developing and implementing theirown solutions * Mathematical equations that are accompanied by a clearexplanation of how the equation was derived The first chapter leads with a compelling argument for studyingnonparametric regression and sets the stage for more advanceddiscussions. In addition to covering standard topics, such askernel and spline methods, the book provides in-depth coverage ofthe smoothing of histograms, a topic generally not covered incomparable texts. With a learning-by-doing approach, each topical chapter includesthorough S-Plus? examples that allow readers to duplicate the sameresults described in the chapter. A separate appendix is devoted tothe conversion of S-Plus objects to R objects. In addition, eachchapter ends with a set of problems that test readers' grasp of keyconcepts and techniques and also prepares them for more advancedtopics. This book is recommended as a textbook for undergraduate andgraduate courses in nonparametric regression. Only a basicknowledge of linear algebra and statistics is required. Inaddition, this is an excellent resource for researchers andengineers in such fields as pattern recognition, speechunderstanding, and data mining. Practitioners who rely onnonparametric regression for analyzing data in the physical,biological, and social sciences, as well as in finance andeconomics, will find this an unparalleled resource.

Development Of Regression Equations For Predicting Body Density Percent Body Fat And Lean Body Mass In Prepubescent Females Age 7 11

Author : Barbara Thogersen
ISBN : OCLC:7920653
Genre : Body composition
File Size : 61. 24 MB
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