<--- Back to Details
First PageDocument Content
Failure / Engineering / Statistics / Engineering statistics / Failure rate / Redundancy / Scientific modelling / Software quality / Fault-tolerant computer system / Survival analysis / Systems engineering / Reliability engineering
Date: 2010-10-25 08:48:34
Failure
Engineering
Statistics
Engineering statistics
Failure rate
Redundancy
Scientific modelling
Software quality
Fault-tolerant computer system
Survival analysis
Systems engineering
Reliability engineering

NOTESProject’s full name:

Add to Reading List

Source URL: www.nks.org

Download Document from Source Website

File Size: 29,31 KB

Share Document on Facebook

Similar Documents

Design Influence on Player Retention : A Method Based on Time Varying Survival Analysis Thibault Allart∗†§ , Guillaume Levieux† , Michel Pierfitte∗ , Agathe Guilloux§ and Stephane Natkin† ∗ Ubisoft Product

DocID: 1vinJ - View Document

Identifying statistically significant combinatorial markers Raissa T. Relator1, Aika Terada2,3,1, Jun Sese*1,4 for survival analysis AIRC, AIST, JST-PRESTO, Univ. of Tokyo, AIST-Tokyo Tech RWBC-OIL 1

DocID: 1vf5G - View Document

CAPE BRETON REGIONAL COHORT-SURVIVAL ANALYSIS Prepared by John Heseltine, MCIP Terrain Group

DocID: 1v7yi - View Document

Southeast Asian J Trop Med Public Health LONG-TERM SURVIVAL OF ISCHEMIC AND HEMORRHAGIC STROKE PATIENTS: AN ANALYSIS OF NATIONAL THAI DATA Nipaporn Butsing1,2, Barbara Mawn3, Nawarat Suwannapong4 and

DocID: 1ukQ1 - View Document

Neural Networks as Statistical Methods in Survival Analysis B.D. Ripley Department of Statistics, University of Oxford and R.M. Ripley

DocID: 1tMjS - View Document