Modified goodness-of-fit test for the laplace distribution

1988 ◽  
Vol 17 (1) ◽  
pp. 275-281 ◽  
Author(s):  
Vincent C. Yen ◽  
Albert H. Moore
Author(s):  
Eke, Charles N ◽  
Osuji, George Amaeze ◽  
Nwosu, Dozie Felix

This study examined the probability distribution that best described the quarterly economic growth rate of Nigeria between 1960- 2015. The study collected secondary data from Central Bank of Nigeria (CBN) Statistical Bulletin 2015 on Gross Domestic Product to compute the economic growth rate of Nigeria. Six theoretical statistical distributions were fitted via Normal Distribution, Logistic Distribution, Laplace Distribution, Cauchy Distribution, Gumbel (Largest Extreme Value) Distribution and Generalized Logistic Distribution. The Laplace Distribution fitted the data as confirmed by Kolmogorov Simonov goodness of fit test, Akaike Information Criteria and Bayes Information Criteria. The probabilities of economic growth rate behaviours were obtained from the best fit distribution. The analysis showed that the chance of obtaining a negative quarterly economic growth rate is 28%. The chance of an economic recession is 8%. Also, the probability of having a positive single digit quarterly economic growth rate is 46%. In addition, having a double digit positive quarterly economic growth rate is 26%.  


2016 ◽  
Vol 119 ◽  
pp. 30-35 ◽  
Author(s):  
Elizabeth González-Estrada ◽  
José A. Villaseñor

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
T Besbes ◽  
S Mleyhi ◽  
J Sahli ◽  
M Messai ◽  
J Ziadi ◽  
...  

Abstract Background Early prediction of patients at highest risk of a poor outcome after cardiovascular surgery, including death can aid medical decision making, and adapt health care management in order to improve prognosis. In this context, we conducted this study to validate the CASUS severity score after cardiac surgery in the Tunisian population. Methods This is a retrospective cohort study conducted among patients who underwent cardiac surgery under extracorporeal circulation during the year 2018 at the Cardiovascular Surgery Department of La Rabta University Hospital in Tunisia. Data were collected from the patients hospitalization records. The discrimination of the score was assessed using the ROC curve and the calibration using the Hosmer-Lemeshow goodness of fit test and then by constructing the calibration curve. Overall correct classification was also obtained. Results In our study, the observed mortality rate was 10.52% among the 95 included patients. The discriminating power of the CASUS score was estimated by the area under the ROC curve (AUC), this scoring system had a good discrimination with AUC greater than 0.9 from postoperative Day 0 to Day 5.From postoperative day 0 to day 5, the Hosmer-Lemeshow's test gave a value of chi square test statistic ranging from 1.474 to 8.42 and a value of level of significance ranging from 0.39 to 0.99 indicating a good calibration. The overall correct classification rate from postoperative day 0 to day 5 ranged from 84.4% to 92.4%. Conclusions Despite the differences in the profile of the risk factors between the Tunisian population and the population constituting the database used to develop the CASUS score, we can say that this risk model presents acceptable performances in our population, attested by adequate discrimination and calibration. Prospective and especially multicentre studies on larger samples are needed before definitively conclude on the performance of this model in our country. Key messages The casus score seems to be valid to predict mortality among patients undergoing cardiac surgery. Multicenter study on larger sample is needed to derive and validate models able to predict in-hospitals mortality.


Test ◽  
2021 ◽  
Author(s):  
Jiming Jiang ◽  
Mahmoud Torabi

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