Missing data management and statistical measurement of socio-economic status: application of big data

Journal of Big Data

Table 2 Result for the estimates of a missing values by linear interpolation, linear spline interpolation and linear regression estimation: in case of two non-sequentially missing values

Year	2000	2001	2002	2003	2004	2005	2006
Y(t)_Actual	41.18	36.69	35.50	38.25	40.05	47.21	48.81
Linear interpolation	41.18	38.34	37.47	37.78	42.73	44.43	47.14
Linear regression estimate	41.18	41.88	41.60	41.00	40.47	40.39	39.89
Linear spline interpolation	41.18	38.34	37.47	37.78	42.73	44.43	47.14
Linear interpolation error	0.00	− 1.65	− 1.96	0.47	− 2.67	2.77	1.67
Linear Reqression error	0.00	− 5.19	− 6.10	− 2.75	− 0.42	6.81	8.92
Linear spline interpolation error	0.00	− 1.65	− 1.96	0.47	− 2.67	2.77	1.67

Year	2007	2008	2009	2010	2011	2012	2013
Y(t)_Actual	47.07	47.97	35.37	38.44	38.79	36.89	33.22
Linear interpolation	48.39	41.22	43.21	37.08	37.67	36.00	33.22
Linear regression estimate	39.77	39.60	39.96	39.20	38.89	38.74	33.22
Linear spline interpolation	48.39	41.22	43.21	37.08	37.67	36.00	33.22
Linear interpolation error	− 1.32	6.75	− 7.84	1.36	1.12	0.89	0.00
Linear Reqression error	7.30	8.37	− 4.58	− 0.75	− 0.10	− 1.85	0.00
Linear spline interpolation error	− 1.32	6.75	− 7.84	1.36	1.12	0.89	0.00