000756048 000__ 04085cam\a2200457Ii\4500
000756048 001__ 756048
000756048 005__ 20230306141954.0
000756048 006__ m\\\\\o\\d\\\\\\\\
000756048 007__ cr\cn\nnnunnun
000756048 008__ 160623s2016\\\\sz\a\\\\ob\\\\000\0\eng\d
000756048 020__ $$a9783319318226$$q(electronic book)
000756048 020__ $$a3319318225$$q(electronic book)
000756048 020__ $$z9783319318202
000756048 035__ $$aSP(OCoLC)ocn952108480
000756048 035__ $$aSP(OCoLC)952108480
000756048 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dYDXCP$$dIDEBK$$dGW5XE$$dEBLCP$$dN$T$$dUPM$$dOCLCF$$dCOO
000756048 049__ $$aISEA
000756048 050_4 $$aHB137
000756048 08204 $$a338.5/4$$223
000756048 1001_ $$aDagum, Estela Bee,$$eauthor.
000756048 24510 $$aSeasonal adjustment methods and real time trend-cycle estimation$$h[electronic resource] /$$cEstela Bee Dagum, Silvia Bianconcini.
000756048 264_1 $$aSwitzerland :$$bSpringer,$$c2016.
000756048 300__ $$a1 online resource (xvi, 283 pages) :$$billustrations.
000756048 336__ $$atext$$btxt$$2rdacontent
000756048 337__ $$acomputer$$bc$$2rdamedia
000756048 338__ $$aonline resource$$bcr$$2rdacarrier
000756048 4901_ $$aStatistics for social and behavioral sciences,$$x2199-7357
000756048 504__ $$aIncludes bibliographical references.
000756048 5050_ $$aIntroduction -- Time Series Components -- Part I: Seasonal Adjustment Methods -- Seasonal Adjustment: Meaning, Purpose and Methods -- Linear Filters Seasonal Adjustment Methods: Census Method II and its Variants -- Seasonal Adjustment Based on ARIMA Decomposition: TRAMO-SEATS -- Seasonal Adjustment Based on Structural Time Series Models -- Part II: Trend-Cycle Estimation -- Trend-Cycle Estimation -- Further Developments on the Henderson Trend-Cycle Filter -- A Unified View of Trend-Cycle Predictors in Reproducing Kernel Hilbert Spaces (RKHS) -- Real Time Trend-Cycle Prediction -- The Effect of Seasonal Adjustment on Real-Time Trend-Cycle Prediction -- Glossary.
000756048 506__ $$aAccess limited to authorized users.
000756048 520__ $$aThis book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
000756048 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 5, 2016).
000756048 650_0 $$aSeasonal variations (Economics)
000756048 650_0 $$aEstimation theory.
000756048 7001_ $$aBianconcini, Silvia,$$eauthor.
000756048 77608 $$iPrint version:$$aBee Dagum, Estela.$$tSeasonal adjustment methods and real time trend-cycle prediction.$$d[Cham, Switzerland] : Springer, c2016$$z9783319318202$$w(DLC)  2016938799
000756048 830_0 $$aStatistics for social and behavioral sciences.
000756048 852__ $$bebk
000756048 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-31822-6$$zOnline Access$$91397441.1
000756048 909CO $$ooai:library.usi.edu:756048$$pGLOBAL_SET
000756048 980__ $$aEBOOK
000756048 980__ $$aBIB
000756048 982__ $$aEbook
000756048 983__ $$aOnline
000756048 994__ $$a92$$bISE