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Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Published by North-Holland Pub. Co, 1972
ISBN 10: 0720431778 ISBN 13: 9780720431773
Language: English
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Hardcover. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Published by North-Holland Pub. Co, 1972
ISBN 10: 0720431778 ISBN 13: 9780720431773
Language: English
Seller: PAPER CAVALIER UK, London, United Kingdom
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Add to basketCondition: good. A good reading copy. May contain markings or be a withdrawn library copy.
Seller: books4less (Versandantiquariat Petra Gros GmbH & Co. KG), Welling, Germany
gebundene Ausgabe. Condition: Gut. 292 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); leichte altersbedingte Anbräunung des Papiers; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut.Text in ALTDEUTSCHER SCHRIFT. Sprache: Deutsch Gewicht in Gramm: 650.
Hardcover. Condition: Bon. Ancien livre de bibliothèque. Traces d'usure sur la couverture. Edition 1972. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Signs of wear on the cover. Edition 1972. Ammareal gives back up to 15% of this item's net price to charity organizations.
Published by North Holland Publishing Company, 1976
ISBN 10: 0072031778 ISBN 13: 9780072031775
Language: English
Seller: MB Books, Derbyshire, United Kingdom
First Edition
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Add to basketHardcover. Condition: Good. No Jacket. 1st Edition. Condition : Good. Hard cover, no jacket. Former university library copy with associated markings. 280pp. No highlighting or annotations to text. Pages age toned. Covered in non removable protective laminate. Photo on request.
Published by North Holland Publishing Company, 1976
Seller: Anybook.com, Lincoln, United Kingdom
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Add to basketCondition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:
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Add to basketCondition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:0720431778.
Published by North-Holland 01.05.1972., 1972
ISBN 10: 0720431778 ISBN 13: 9780720431773
Language: English
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Add to basketGebundene Ausgabe. Condition: Gut. 292 Seiten ex Library Book aus einer wissenschafltichen Bibliothek Sprache: Englisch Gewicht in Gramm: 550.
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Add to basketCondition: Good. Volume 192. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,400grams, ISBN:3540108386.
Published by North-Holland 01.05.1972., 1972
ISBN 10: 0720431778 ISBN 13: 9780720431773
Language: English
Seller: NEPO UG, Rüsselsheim am Main, Germany
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Add to basketGebundene Ausgabe. Condition: Gut. 292 Seiten Exemplar aus einer wissenchaftlichen Bibliothek Sprache: Englisch Gewicht in Gramm: 550.
Published by North-Holland Amsterdam,, 1972
ISBN 10: 0720431778 ISBN 13: 9780720431773
Language: English
Seller: Bernhard Kiewel Rare Books, Grünberg, Germany
23 x 16. 280 Seiten. Hardcover. Ordnungsgemäß aus einer Universitäts-Bibliothek ausgesondert (Stempel, Rückenschild). Gut erhaltenes Exemplar. Sprache: Englisch Gewicht in Gramm: 800.
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Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 1981
ISBN 10: 3540108386 ISBN 13: 9783540108382
Language: English
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and non linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate if the distributions of both the errors and the regressors have fat tails. This study also improves and extends the NL2SLSE theory of Amemiya. The method involved is a variant of the instrumental variables method, requiring at least as many instrumental variables as parameters to be estimated. The new MIE method requires less instrumental variables. Asymptotic normality can be derived by employing only one instrumental variable and consistency can even be proved with out using any instrumental variables at all. This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and nonA linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate if the distributions of both the errors and the regressors have fat tails. This study also improves and extends the NL2SLSE theory of Amemiya. The method involved is a variant of the instrumental variables method, requiring at least as many instrumental variables as parameters to be estimated. The new MIE method requires less instrumental variables. Asymptotic normality can be derived by employing only one instrumental variable and consistency can even be proved withA out using any instrumental variables at al Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: As New. Unread book in perfect condition.
Published by North Holland Publishing Company, 1976
Seller: Anybook.com, Lincoln, United Kingdom
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Add to basketCondition: Fair. Volume 77. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:
Published by Springer, Berlin, 1981
Language: English
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Add to basketSoftcover. Condition: Sehr gut. Berlin, Springer 1981 gr.8°. 198 p. Pbck. Lecture Notes in Economics and Mathematical Systems, 192.- Throughout slightly browned.
Published by Berlin ; New York: Springer-Verlag, 1981, 1981
Seller: Steven Wolfe Books, Newton Centre, MA, U.S.A.
Bierens, Herman J., 1943-. Robust methods and asymptotic theory in nonlinear econometrics. Berlin ; New York: Springer-Verlag, 1981, ix, 198pp., PAPERBACK, very good BUT with a library gift donation stamp inside front cover and previous owner's initials on cover, but book was never part of the library, just a gift. Lecture notes in economics and mathematical systems, 192. 9783540108382 ISBN 0387108386.
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Published by Springer Berlin Heidelberg 1981-01-01, 1981
ISBN 10: 3540108386 ISBN 13: 9783540108382
Language: English
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Add to basketPaperback. Condition: New.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 216.
Published by Springer Berlin Heidelberg, 1981
ISBN 10: 3540108386 ISBN 13: 9783540108382
Language: English
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketPaperback. Condition: Brand New. 207 pages. German language. 9.53x6.54x0.55 inches. In Stock.
Published by North- Holland Amsterdam, 1972
Language: English
Seller: ralfs-buecherkiste, Herzfelde, MOL, Germany
Hardcover. Condition: Gut. 280 S. Economics Numerical Optimization Least Squares Theory Confidence Interval Maximum Likelhood Estimation Heteroscedasticity Cobb- Douglas Type Function Guter Zustand/ Good Ex-Library. With figures. Cover shows mild wear. ha1062947 Sprache: Englisch Gewicht in Gramm: 640.
Published by Springer Berlin Heidelberg, 1981
ISBN 10: 3540108386 ISBN 13: 9783540108382
Language: English
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and non linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate if the distributions of both the errors and the regressors have fat tails. This study also improves and extends the NL2SLSE theory of Amemiya. The method involved is a variant of the instrumental variables method, requiring at least as many instrumental variables as parameters to be estimated. The new MIE method requires less instrumental variables. Asymptotic normality can be derived by employing only one instrumental variable and consistency can even be proved with out using any instrumental variables at all.
Seller: Buchpark, Trebbin, Germany
Condition: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher.
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 1981
ISBN 10: 3540108386 ISBN 13: 9783540108382
Language: English
Seller: AussieBookSeller, Truganina, VIC, Australia
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Add to basketPaperback. Condition: new. Paperback. This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and non linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate if the distributions of both the errors and the regressors have fat tails. This study also improves and extends the NL2SLSE theory of Amemiya. The method involved is a variant of the instrumental variables method, requiring at least as many instrumental variables as parameters to be estimated. The new MIE method requires less instrumental variables. Asymptotic normality can be derived by employing only one instrumental variable and consistency can even be proved with out using any instrumental variables at all. This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and nonA linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate if the distributions of both the errors and the regressors have fat tails. This study also improves and extends the NL2SLSE theory of Amemiya. The method involved is a variant of the instrumental variables method, requiring at least as many instrumental variables as parameters to be estimated. The new MIE method requires less instrumental variables. Asymptotic normality can be derived by employing only one instrumental variable and consistency can even be proved withA out using any instrumental variables at al Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Springer, Springer Jun 1981, 1981
ISBN 10: 3540108386 ISBN 13: 9783540108382
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and non linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate if the distributions of both the errors and the regressors have fat tails. This study also improves and extends the NL2SLSE theory of Amemiya. The method involved is a variant of the instrumental variables method, requiring at least as many instrumental variables as parameters to be estimated. The new MIE method requires less instrumental variables. Asymptotic normality can be derived by employing only one instrumental variable and consistency can even be proved with out using any instrumental variables at all. 216 pp. Englisch.
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Add to basketCondition: New. Print on Demand pp. 216 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam.
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Condition: New. PRINT ON DEMAND pp. 216.