rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Applied Nonparametric Statistics in Reliability
  name:
    name part: Gámiz, M. Luz.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Kulasekera, K. B.
    role:
      role term: author.
  name:
    name part: Limnios, Nikolaos.
    role:
      role term: author.
  name:
    name part: Lindqvist, Bo Henry.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 230 p. online resource.
  abstract: Nonparametric 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.
  table of contents: 1. 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.
  note: by M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist.
  subject:
    topic: Engineering
  subject:
    topic: Statistics
  subject:
    topic: Quality control
  subject:
    topic: Reliability
  subject:
    topic: Industrial safety
  subject:
    topic: Engineering
  subject:
    topic: Quality Control, Reliability, Safety and Risk
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  classification: TA169.7
  classification: T55-T55.3
  classification: TA403.6
  classification: 658.56
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Series in Reliability Engineering
  identifier: 9780857291189
  identifier: http://dx.doi.org/10.1007/978-0-85729-118-9
  record info:
    record creation date: 110211
    record change date: 20151030021320.0
    record identifier: 978-0-85729-118-9