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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

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

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