000 03087nam a22004695i 4500
001 978-1-4614-4738-2
003 DE-He213
005 20140220083250.0
007 cr nn 008mamaa
008 120723s2012 xxu| s |||| 0|eng d
020 _a9781461447382
_9978-1-4614-4738-2
024 7 _a10.1007/978-1-4614-4738-2
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aPizzinga, Adrian.
_eauthor.
245 1 0 _aRestricted Kalman Filtering
_h[electronic resource] :
_bTheory, Methods, and Application /
_cby Adrian Pizzinga.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2012.
300 _aX, 62 p. 9 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Statistics,
_x2191-544X ;
_v12
505 0 _aIntroduction -- Linear state space models and the Kalman filtering: a briefing -- Restricted Kalman filtering: theoretical issues -- Restricted Kalman filtering: methodological issues -- Applications -- Further Extensions.
520 _aIn statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone.  This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and applications in investment analysis and macroeconomics, where the proposed methods are illustrated and evaluated. The Brief has a short chapter on linear state space models and the Kalman filter, aiming to make the book self-contained and to give a quick reference to the reader (notation and terminology). The prerequisites would be a contact with time series analysis in the level of Hamilton (1994) or Brockwell & Davis (2002) and also with linear state models and the Kalman filter – each of these books has a chapter entirely dedicated to the subject. The book is intended for graduate students, researchers and practitioners in statistics (specifically: time series analysis and econometrics).
650 0 _aStatistics.
650 0 _aMathematical statistics.
650 0 _aEconomics
_xStatistics.
650 1 4 _aStatistics.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aStatistics, general.
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461447375
830 0 _aSpringerBriefs in Statistics,
_x2191-544X ;
_v12
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-4738-2
912 _aZDB-2-SMA
999 _c101514
_d101514