000 03555nam a22005055i 4500
001 978-0-85729-118-9
003 DE-He213
005 20140220083712.0
007 cr nn 008mamaa
008 110211s2011 xxk| s |||| 0|eng d
020 _a9780857291189
_9978-0-85729-118-9
024 7 _a10.1007/978-0-85729-118-9
_2doi
050 4 _aTA169.7
050 4 _aT55-T55.3
050 4 _aTA403.6
072 7 _aTGPR
_2bicssc
072 7 _aTEC032000
_2bisacsh
082 0 4 _a658.56
_223
100 1 _aGámiz, M. Luz.
_eauthor.
245 1 0 _aApplied Nonparametric Statistics in Reliability
_h[electronic resource] /
_cby M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist.
264 1 _aLondon :
_bSpringer London,
_c2011.
300 _aXIII, 230p. 41 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Reliability Engineering,
_x1614-7839
505 0 _a1. Lifetime Data -- 2. Models for Perfect Repair -- 3. Models for Minimal Repair -- 4. Models for Imperfect Repair -- 5. Systems with Multi-components -- 6. Reliability of Semi–Markov Systems -- 7. Hazard Regression Analysis.
520 _aNonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored. Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. The scope of the book includes: smooth estimation of the reliability function and hazard rate of non-repairable systems; study of stochastic processes for modelling the time evolution of systems when imperfect repairs are performed; nonparametric analysis of discrete and continuous time semi-Markov processes; isotonic regression analysis of the structure function of a reliability system, and lifetime regression analysis. Besides the explanation of the mathematical background, several numerical computations or simulations are presented as illustrative examples. The corresponding computer-based methods have been implemented using R and MATLAB®. A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted. Applied Nonparametric Statistics in Reliability will serve the practical needs of scientists (statisticians and engineers) working on applied reliability subjects.
650 0 _aEngineering.
650 0 _aSystem safety.
650 1 4 _aEngineering.
650 2 4 _aQuality Control, Reliability, Safety and Risk.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
700 1 _aKulasekera, K. B.
_eauthor.
700 1 _aLimnios, Nikolaos.
_eauthor.
700 1 _aLindqvist, Bo Henry.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780857291172
830 0 _aSpringer Series in Reliability Engineering,
_x1614-7839
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-85729-118-9
912 _aZDB-2-ENG
999 _c105134
_d105134