Kunitomo (61 resultados)

Paperback. Condición: New.

Paperback Shinsho. Condición: Brand New. 6.77x4.17x0.71 inches. In Stock.

gebundene Ausgabe. Condición: Gut. 261 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.). Schnitt und Einband sind etwas staubschmutzig; Einbandkanten sind leicht bestossen; Seiten ungleich geschnitten; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. Sprache: Englisch Gewicht in Gramm: 490. …

Paperback Shinsho. Condición: Brand New. Japanese language. 6.85x4.57x0.71 inches. In Stock.

Softcover. First Edition; First Printing. Very Good+ in wrappers. Japanese import.; 8vo 8" - 9" tall.

Softcover. First Edition; First Printing. Very Good+ in wrappers. Japanese import.; 8vo 8" - 9" tall.

Softcover. First Edition; First Printing. Very Good+ in wrappers. Japanese import.; 8vo 8" - 9" tall.

Paperback. Condición: Brand New. 213 pages. Japanese language. 7.48x5.28x0.79 inches. In Stock.

No jacket. Condición: Bon. Ancien livre de bibliothèque avec équipements. Sans jaquette. Couverture différente. Edition 1974. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. No dust jacket. Different cover. Edition 1974. Ammareal gives back up to 15% of this item's net price to charity organizations. …

Condición: Good. Unmarked hardcover in unclipped jacket. Some average wear and smudging to jacket. Boards are excellent. Markings in pen and marker on front cover flap. Pages are clean and binding is tight.

Tankobon Hardcover. Condición: Brand New. Japanese language. 8.27x5.83x0.39 inches. In Stock.

Condición: New. pp.

Condición: New.

Condición: New.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book, we explain the development of a new filtering method to estimate the hidden states of random variables for multiple non-stationary time series data. This method is particularly helpful in analyzing small-sample non-stationary macro-economic time series. The method is based on the frequency-domain application of the separating information maximum likelihood (SIML) method, which was proposed by Kunitomo, Sato, and Kurisu (Springer, 2018) for financial high-frequency time series. We solve the filtering problem of hidden random variables of trend-cycle, seasonal, and measurement-error components and propose a method to handle macro-economic time series. The asymptotic theory based on the frequency-domain analysis for non-stationary time series is developed with illustrative applications, including properties of the method of Muller and Watson (2018), and analyses of macro-economic data in Japan.Vast research has been carried out on the use of statistical time series analysis for macro-economic time series. One important feature of the series, which is different from standard statistical time series analysis, is that the observed time series is an apparent mixture of non-stationary and stationary components. We apply the SIML method for estimating the non-stationary errors-in-variables models. As well, we discuss the asymptotic and finite sample properties of the estimation of unknown parameters in the statistical models. Finally, we utilize their results to solve the filtering problem of hidden random variables and to show that they lead to new a way to handle macro-economic time series.…

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics.Considerable interest has been given to the estimation problem of integrated volatility and covariance by using high-frequency financial data. Although several new statistical estimation procedures have been proposed, each method has some desirable properties along with some shortcomings that call for improvement. For estimating integrated volatility, covariance, and the related statistics by using high-frequency financial data, the SIML method has been developed by Kunitomo and Sato to deal with possible micro-market noises.The authors show that the SIML estimator has reasonable finite sample properties as well as asymptotic properties in the standard cases. It is also shown that the SIML estimator has robust properties in the sense that it is consistent and asymptotically normal in the stable convergence sense when there are micro-market noises, micro-market (non-linear) adjustments, and round-off errors with the underlying (continuous time) stochastic process. Simulation results are reported in a systematic way as are some applications of the SIML method to the Nikkei-225 index, derived from the major stock index in Japan and the Japanese financial sector.…

Tankobon Hardcover. Condición: Brand New. Japanese language. 8.27x5.91x0.71 inches. In Stock.

Paperback. Condición: Brand New. 124 pages. 9.25x6.10x0.32 inches. In Stock.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: Très bon. Merci, votre achat aide à financer des programmes de lutte contre l'illettrisme.

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Taschenbuch. Condición: Neu. The SIML Filtering Method for Noisy Non-stationary Economic Time Series | Naoto Kunitomo (u. a.) | Taschenbuch | SpringerBriefs in Statistics | x | Englisch | 2025 | Springer | EAN 9789819608812 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Condición: Neu. Separating Information Maximum Likelihood Method for High-Frequency Financial Data | Naoto Kunitomo (u. a.) | Taschenbuch | viii | Englisch | 2018 | Springer Japan | EAN 9784431559283 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Condición: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9782302097889.

Condición: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9782302102750.

Condición: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9782302105966.

Condición: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9782302103825.

Condición: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9782302103894.