000			03502nam a22004695i 4500
001			978-0-85729-118-9
003			DE-He213
005			20251006084442.0
007			cr nn 008mamaa
008			110211s2011 xxk| s |||| 0|eng d
020			_a9780857291189
020			_a99780857291189
024	7		_a10.1007/978-0-85729-118-9 _2doi
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 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-ENG
942			_2ddc _cER
999			_c59950 _d59950