Table 2b.

Empirical Results of Quartic Model of Deaths with K $=$ 100.

Name	$y_{max}$	$\hat{\mu }$	$\hat{\gamma }$	Mon	Tue	Wed	Thu	Fri	Sat	log_likelihood
USA	1885	132	−42.44	−0.34	−0.25	0.22	0.29	0.03	0.15	−94.9***
	(2730)	(171)	(4.31)	(0.25)	(0.25)	(0.25)	(0.25)	(0.25)	(0.25)
Brazil	1057	194	−3	−0.41	−0.31	0.19	0.1	0.17	0.08	19.77***
	(402)	(39)	(0.35)	(0.08)	(0.08)	(0.08)	(0.08)	(0.08)	(0.08)
Russia	146	189	−3.8	0	−0.14	0.2	0.21	0.24	0.26	−30.11**
	(101)	(72)	(0.68)	(0.13)	(0.13)	(0.13)	(0.13)	(0.13)	(0.13)
India	414	241	−0.79	0.14	0.01	0.18	0.13	0.07	0.08	−46.97**
	(140)	(37)	(0.22)	(0.15)	(0.15)	(0.15)	(0.15)	(0.15)	(0.15)
UK	643	126	−39.88	−0.69	−0.61	0.29	0.22	0.1	0.14	−90.82*
	(730)	(136)	(3.83)	(0.24)	(0.24)	(0.24)	(0.24)	(0.24)	(0.24)
Peru	199	193	−2.85	−0.29	−0.82	−0.32	0.01	−0.07	−0.1	−117.82**
	(269)	(158)	(1.43)	(0.31)	(0.31)	(0.31)	(0.31)	(0.31)	(0.31)
Chile	125	250	−0.55	0.13	−0.46	−0.62	−0.04	−0.02	0.01	−108.52*
	(61)	(63)	(0.35)	(0.29)	(0.29)	(0.29)	(0.28)	(0.28)	(0.29)
Spain	1417	0	−0.56	0.69	0.82	0.18	0.21	0.67	0.2	−153.01**
	(495)	(93)	(0.51)	(0.45)	(0.45)	(0.44)	(0.44)	(0.45)	(0.45)
Italy	903	0	−0.38	−0.36	−0.29	−0.17	−0.1	−0.05	−0.05	−8.6*
	(191)	(22)	(0.12)	(0.11)	(0.11)	(0.11)	(0.1)	(0.1)	(0.11)
Iran	77	130	13.89	−0.02	0.04	0.03	0.05	0.03	−0.36	−75.17*
	(89)	(124)	(3.36)	(0.2)	(0.2)	(0.2)	(0.2)	(0.2)	(0.2)
Mexico	586	219	−1.62	−0.38	−0.1	0.22	0.3	0.23	0.29	−45.97**
	(264)	(48)	(0.34)	(0.15)	(0.15)	(0.15)	(0.15)	(0.15)	(0.15)
France	499	17	−0.59	−0.37	0.35	0.77	0.19	0.34	0.21	−94.57*
	(256)	(62)	(0.38)	(0.25)	(0.25)	(0.25)	(0.24)	(0.24)	(0.25)
Pakistan	116	250	−0.53	0.02	0	0.06	−0.12	−0.01	−0.15	−73.2*
	(46)	(44)	(0.25)	(0.2)	(0.2)	(0.2)	(0.2)	(0.2)	(0.2)
Turkey	70	129	−35.23	−0.01	−0.02	−0.02	0.01	0.06	−0.04	−88.75*
	(79)	(133)	(3.75)	(0.23)	(0.23)	(0.23)	(0.23)	(0.23)	(0.23)
Germany	80	122	−39.19	−0.24	0.61	0.88	0.66	0.45	0.5	−139.68*
	(153)	(272)	(6.8)	(0.39)	(0.39)	(0.39)	(0.38)	(0.38)	(0.39)
Saudi Arabia	40	250	−0.41	−0.09	−0.24	−0.06	−0.15	−0.05	−0.28	−56.95*
	(14)	(37)	(0.21)	(0.17)	(0.17)	(0.17)	(0.17)	(0.17)	(0.17)
Bangladesh	48	250	−0.47	−0.11	−0.09	−0.09	−0.02	−0.14	−0.15	−71.67*
	(19)	(43)	(0.24)	(0.2)	(0.2)	(0.2)	(0.19)	(0.19)	(0.2)
South Africa	2	0	0.5	−0.21	0.16	−0.14	0.16	0.09	0.3	−102.88*
	(1)	(56)	(0.31)	(0.27)	(0.27)	(0.27)	(0.27)	(0.27)	(0.27)
Canada	150	132	−55.41	−0.42	−0.41	−0.23	−0.02	0.02	−0.04	−60.63**
	(164)	(119)	(3.04)	(0.18)	(0.18)	(0.18)	(0.17)	(0.17)	(0.18)
Qatar	1	1	0.16	0.2	0.04	0.1	0.11	0.01	0.18	−59.86
	(0 )	(37)	(0.2)	(0.18)	(0.18)	(0.18)	(0.17)	(0.17)	(0.18)
Colombia	69	250	−0.45	0.07	−0.03	−0.02	−0.15	−0.23	0.09	−87.21*
	(30)	(51)	(0.28)	(0.23)	(0.23)	(0.23)	(0.23)	(0.23)	(0.23)
Sweden	47	129	−43.7	−1.47	0.35	0.99	1.24	0.67	0.73	−116.64**
	(63)	(176)	(4.96)	(0.31)	(0.31)	(0.31)	(0.3)	(0.3)	(0.31)
Egypt	66	250	−0.36	−0.18	−0.12	−0.09	−0.52	−0.16	−0.2	−111.47*
	(34)	(64)	(0.36)	(0.29)	(0.29)	(0.29)	(0.29)	(0.29)	(0.29)
Belgium	128	66	−2.61	−0.02	−0.04	0.3	0.39	0.22	0.36	−123.1*
	(176)	(183)	(1.72)	(0.33)	(0.33)	(0.33)	(0.32)	(0.32)	(0.33)
Belarus	7	177	−2.36	−0.04	0.02	−0.1	−0.09	0.09	−0.12	−23.64***
	(6)	(94)	(1)	(0.12)	(0.12)	(0.12)	(0.12)	(0.12)	(0.12)
Argentina	26	250	−0.29	−0.65	0.04	−0.14	0.01	0.01	−0.09	−79.16*
	(11)	(47)	(0.26)	(0.21)	(0.21)	(0.21)	(0.21)	(0.21)	(0.21)
Ecuador	48	150	−9.62	0.12	−0.05	−0.05	0.26	−0.54	0.79	−165.18***
	(234)	(876)	(13.38)	(0.5)	(0.5)	(0.5)	(0.49)	(0.49)	(0.5)
Indonesia	51	250	−0.2	0.05	−0.27	−0.2	−0.28	0.03	−0.04	−74.63**
	(20)	(45)	(0.25)	(0.2)	(0.2)	(0.2)	(0.2)	(0.2)	(0.2)
Netherlands	147	32	−0.93	−0.56	−0.79	0.16	−0.03	−0.02	0.05	−84.25*
	(86)	(67)	(0.46)	(0.22)	(0.22)	(0.22)	(0.22)	(0.22)	(0.22)
UAE	5	133	−22.67	−0.01	0.14	0.09	0.06	0.06	−0.04	−82.18*
	(6)	(153)	(3.83)	(0.22)	(0.22)	(0.22)	(0.22)	(0.22)	(0.22)

This table uses the latest K $=$ 100 days’ (until 2020-06-26) data to fit the quartic model.

Standard errors are in parentheses below the estimates.

$\hat{\mu }$ is the estimated day of the peak, taking 2020-12-31 as day 0.

The number of * at the last column denotes the relative goodness of fit based on log likelihood, where *** indicates the model of the best fit among others.