Amirkabir University of Technology Amirkabir Journal of Civil Engineering 2588-297X 50 1 2018 04 21 Modeling the Intra City Tours with Work Purpose by Using Weighted Multiple Regressions Modeling the Intra City Tours with Work Purpose by Using Weighted Multiple Regressions 139 148 699 10.22060/ceej.2016.699 FA A. R. Mahpour Road, Housing and Development Research Center (BHRC), Tehran, Iran S. Seyedabrishami Faculty of Civil & Environmental Engineering, Tarbiat Modares University, Tehran, Iran 0000-0002-9301-5417 A. R. Mamdoohi Faculty of Civil & Environmental Engineering, Tarbiat Modares University, Tehran, Iran A. H. Baghestani Faculty of Civil & Environmental Engineering, Tarbiat Modares University, Tehran, Iran Journal Article 2015 11 30 In this paper by using the aggregate socioeconomic features of each zone and considering the land use prosperities, the aggregate zonal tours were modeled. For that, classic 4-step modeling database was utilized in which less data collection cost needs. Due heteroscedasticity , appling weighted least square (WLS) method led to multiple weighted regressions by two exogenous independent variables; population and number of employers in zone. Heteroscedasticity affect the efficiency of regression. In comparing of two model, the F test of WLS method growth 27 percent and the amount t students for population reduced from 2.79 to 2.27 that in negligible. On the other hand, the amount of t students for number of employers increases from 2.62 to 3.40 (30 percent). Constant coefficient is negative but in comparison with the maximum number of observed tours (7202 tours) is 0.069 percent and the average number of observed tours (1386 tours) is 0.36 percent that is negligible and the R2 goodness of fit index is 0.927 and acceptable. In this paper by using the aggregate socioeconomic features of each zone and considering the land use prosperities, the aggregate zonal tours were modeled. For that, classic 4-step modeling database was utilized in which less data collection cost needs. Due heteroscedasticity , appling weighted least square (WLS) method led to multiple weighted regressions by two exogenous independent variables; population and number of employers in zone. Heteroscedasticity affect the efficiency of regression. In comparing of two model, the F test of WLS method growth 27 percent and the amount t students for population reduced from 2.79 to 2.27 that in negligible. On the other hand, the amount of t students for number of employers increases from 2.62 to 3.40 (30 percent). Constant coefficient is negative but in comparison with the maximum number of observed tours (7202 tours) is 0.069 percent and the average number of observed tours (1386 tours) is 0.36 percent that is negligible and the R2 goodness of fit index is 0.927 and acceptable. https://ceej.aut.ac.ir/article_699_afd4836712c5e77550897e25711e1d96.pdf