Application of variable selection and dimension reduction on predictors of MSE’s development

Journal of Big Data

Table 9 Linear regression of number of employer in an enterprise based on principal factors

Full model					Reduced model by stepwise elimination
Coefficients	Estimate	Std. error	t value	Pr(\(>\|\hbox {t}\|\))	Coefficients	Estimate	Std. error	t value	Pr(\(>\|\hbox {t}\|\))
(Intercept)	0.762	1.441	0.529	0.597	(Intercept)	0.793	0.284	2.788	0.006
x1	− 0.002	0.013	− 0.115	0.909	x1	Removed
x2	0.007	0.013	0.528	0.598	x2	Removed
x3	0.042	0.082	0.516	0.606	x3	Removed
x4	0.000	0.000	0.442	0.659	x4	Removed
x5	− 0.257	0.026	− 10.063	0.000	x5	0.132	0.035	3.765	0.000
x6	0.245	0.022	11.289	0.000	x6	0.270	0.021	12.963	0.000
x7	0.014	0.096	0.144	0.886	x7	0.067	0.025	2.741	0.007
x8	0.936	0.067	13.954	0.000	x8	Removed
x9	− 0.106	1.070	− 0.099	0.921	x9	− 0.134	0.023	− 5.781	0.000
x10	0.000	0.000	1.864	0.064	x10	1.066	0.041	25.716	0.000
x11	0.066	0.025	2.623	0.010	x11	0.313	0.056	5.612	0.000
Multiple R-squared		0.853			Multiple R-squared		0.852
Adjusted R-squared		0.844			Adjusted R-squared		0.847
F-statistic		88.280			F-statistic		164.700
P-value		< 2.2e−16			P-value		< 2.2e−16