PMID- 31517082
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20201001
IS  - 2405-8440 (Print)
IS  - 2405-8440 (Electronic)
IS  - 2405-8440 (Linking)
VI  - 5
IP  - 8
DP  - 2019 Aug
TI  - Goodness-of-fit tests for the Compound Rayleigh distribution with application to 
      real data.
PG  - e02225
LID - 10.1016/j.heliyon.2019.e02225 [doi]
LID - e02225
AB  - An important problem in statistics is to obtain information about the form of the 
      population from which the sample is drawn. Goodness of fit (GOF) tests is 
      employed to determine how well the observed sample data "fits" some proposed 
      model. The well known standard goodness of fit tests; Kolomogorov-Smirnov (KS), 
      Cramer von Mises (CVM) and Anderson-(AD) tests are used for continuous 
      distributions. When the parameters are unknown, the standard tables for these 
      tests are not valid. The complete sample procedures of goodness of fit tests are 
      inappropriate for use with censored samples. The critical values obtained from 
      published tables of the complete sample test statistic are necessarily 
      conservative. In this paper, we obtain the tables of critical values of modified 
      Kolmogorov-Smirnov (KS) test, Cramer-Von Mises (CVM) test and Anderson-Darling 
      (AD) test for the Compound Rayleigh (CR) distribution with unknown parameters in 
      the case of complete and type II censored samples. Furthermore, we present power 
      comparison between KS test, CVM test and AD test for a number of alternative 
      distributions. Applications of the considered distribution to real medical data 
      sets given by Stablein et al. (1981) are presented.
FAU - Badr, Majdah M
AU  - Badr MM
AD  - Statistics Department, Faculty of Science for Girls, University of Jeddah, P. O. 
      Box 70973, Jeddah, 21577, Saudi Arabia.
LA  - eng
PT  - Journal Article
DEP - 20190828
PL  - England
TA  - Heliyon
JT  - Heliyon
JID - 101672560
PMC - PMC6728302
OTO - NOTNLM
OT  - Applied mathematics
OT  - Censored sample
OT  - Compound Rayleigh distribution
OT  - Computational mathematics
OT  - Goodness of fit test
OT  - Monte Carlo simulation
OT  - Power function
OT  - Statistics
EDAT- 2019/09/14 06:00
MHDA- 2019/09/14 06:01
PMCR- 2019/08/28
CRDT- 2019/09/14 06:00
PHST- 2018/09/13 00:00 [received]
PHST- 2018/12/09 00:00 [revised]
PHST- 2019/07/31 00:00 [accepted]
PHST- 2019/09/14 06:00 [entrez]
PHST- 2019/09/14 06:00 [pubmed]
PHST- 2019/09/14 06:01 [medline]
PHST- 2019/08/28 00:00 [pmc-release]
AID - S2405-8440(19)35885-2 [pii]
AID - e02225 [pii]
AID - 10.1016/j.heliyon.2019.e02225 [doi]
PST - epublish
SO  - Heliyon. 2019 Aug 28;5(8):e02225. doi: 10.1016/j.heliyon.2019.e02225. eCollection 
      2019 Aug.