Table 5.

Parameter estimates and goodness of fit statistics for COVID-19 data

Model	MLEs	−log L	AIC	BIC	$W^{\ast }$	$A^{\ast }$	K-S	$pvalue$
$GPU{D}_{(J-S)}$	$\widehat{\theta }=1.382$	996.80	1987.6	1972.55	0.040	0.286	0.015	0.93
	$\widehat{\alpha }=0.017$
	$\widehat{k}=1.355$
Weibull	$\widehat{\lambda }=1.526$	1049.43	2102.87	2112.90	1.215	7.836	0.063	0.000
	$\widehat{\beta }=0.017$
EW	$\widehat{\alpha }=4.659$	1009.16	2024.32	2039.37	0.109	0.842	0.024	0.539
	$\widehat{\lambda }=15.68$
	$\widehat{\gamma }=0.800$
NMOW	$\widehat{\theta }=23.594$	1012.29	2030.59	2045.63	0.062	0.433	0.017	0.892
	$\widehat{\lambda }=4.784$
	$\widehat{\beta }=2.490$
KwEW	$\widehat{\alpha }=5.135$	1008.85	2027.70	2052.78	0.115	0.883	0.024	0.507
	$\widehat{\gamma }=0.867$
	$\widehat{k}=0.714$
	$\widehat{\beta }=5.990$
	$\widehat{\lambda }=4.440$
APTW	$\widehat{\alpha }=0.008$	998.913	2003.82	2018.87	0.371	2.432	0.031	0.222
	$\widehat{\beta }=5.334$
	$\widehat{\lambda }=1.893$
EEW	$\widehat{\lambda }=5.577$	1010.26	2028.53	2048.58	0.121	0.804	0.020	0.728
	$\widehat{\alpha }=2.691$
	$\widehat{\beta }=1.118$
	$\widehat{\gamma }=0.253$