# first, we employed a R code to modify the database (.dat)
# install.packages("dplyr")
# install.packages("readr")
library(dplyr)
library(readr)
setwd("C:/Users/manud/OneDrive/Escritorio/t-cons/dat")
# Load required libraries
library(dplyr)
library(readr)
# Read the tab-delimited .dat file
data <- read_delim("CARPOOL_24_25.dat", delim = "\t", col_types = cols(.default = col_double()))
# Precompute CAMPUS (1 if V4 == 1, 0 otherwise)
data <- data %>%
mutate(CAMPUS = as.integer(V4 == 1))
# Precompute MEDIA and CMED
data <- data %>%
mutate(MEDIA = (V16 + V17 + V18 + V19 + V20 + V21) / 6,
CMED = as.integer(MEDIA > 3))
# Verify the new columns
summary(data$CAMPUS)
summary(data$MEDIA)
summary(data$CMED)
# Save the updated .dat file
write_delim(data, "CARPOOL_24_25_updated.dat", delim = "\t", na = "NA")
# Optional: Check the first few rows of the updated file
head(data[, c("V4", "CAMPUS", "V16", "V17", "V18", "V19", "V20", "V21", "MEDIA", "CMED")])
1# multinomial logit model – basic model
// This file has automatically been generated.
// 05/20/25 16:28:06
// Michel Bierlaire, EPFL
biogeme 2.0 [Sat Oct 30 17:26:53 CEDT 2010]
Michel Bierlaire, EPFL
Modelo COCHE COMPARTIDO
Model: Multinomial Logit
Number of estimated parameters: 7
Number of observations: 1608
Number of individuals: 1608
Null log-likelihood: -1766.569
Cte log-likelihood: -1717.085
Init log-likelihood: -1766.569
Final log-likelihood: -1618.855
Likelihood ratio test: 295.427
Rho-square: 0.084
Adjusted rho-square: 0.080
Final gradient norm: +7.449e-003
Diagnostic: Convergence reached...
Iterations: 11
Run time: 00:00
Variance-covariance: from analytical hessian
Sample file: CARPOOL_24_25.dat
Utility parameters
******************
Name Value Std err t-test p-val Rob. std err Rob. t-test Rob. p-val
---- ----- ------- ------ ----- ------------ ----------- ----------
ASC1 0.00 --fixed--
ASC2 0.00 --fixed--
ASC3 -0.986 0.137 -7.18 0.00 0.144 -6.83 0.00
CT -0.0725 0.0225 -3.23 0.00 0.0228 -3.18 0.00
IN 0.0718 0.0603 1.19 0.23 * 0.0600 1.20 0.23 *
PF 0.362 0.0607 5.97 0.00 0.0603 6.01 0.00
PK -0.0304 0.00756 -4.02 0.00 0.00750 -4.06 0.00
TE -0.471 0.0414 -11.36 0.00 0.0421 -11.18 0.00
TV 0.00253 0.00274 0.92 0.36 * 0.00290 0.87 0.38 *
Utility functions
*****************
3 NINGUNA AV3 ASC3 * one
1 OPCION1 AV1 ASC1 * one + CT * CTV1 + TV * T1 + PK * PK1 + TE * TE1 + PF * PF1 + IN * IN1
2 OPCION2 AV2 ASC2 * one + CT * CTV2 + TV * T2 + PK * PK2 + TE * TE2 + PF * PF2 + IN * IN2
Correlation of coefficients
***************************
Coeff1 Coeff2 Covariance Correlation t-test Rob. covar. Rob. correl. Rob. t-test
------ ------ ---------- ----------- ------ ----------- ------------ -----------
IN TV -2.38e-007 -0.00144 1.15 * 9.54e-007 0.00549 1.15 *
IN PK -1.97e-005 -0.0433 1.67 * -3.38e-006 -0.00752 1.69 *
CT PK -4.52e-006 -0.0266 -1.76 * -1.21e-006 -0.00706 -1.75 *
CT IN 3.91e-006 0.00289 -2.25 -2.73e-005 -0.0200 -2.23
CT TV -1.26e-005 -0.206 -3.24 -1.21e-005 -0.184 -3.20
IN PF 0.000133 0.0363 -3.46 0.000302 0.0836 -3.57
ASC3 TE 0.00117 0.206 -3.82 0.00138 0.227 -3.66
PK TV 2.20e-007 0.0107 -4.11 -4.56e-007 -0.0210 -4.07
PF TV -1.52e-006 -0.00917 5.92 -4.08e-006 -0.0233 5.95
PF PK -1.81e-005 -0.0394 6.39 -2.46e-005 -0.0543 6.42
CT PF -2.68e-005 -0.0197 -6.67 -4.66e-005 -0.0339 -6.67
ASC3 CT 0.000887 0.288 -6.89 0.00100 0.304 -6.56
ASC3 PK 0.000310 0.299 -7.07 0.000297 0.274 -6.70
IN TE -0.000106 -0.0426 7.27 -0.000133 -0.0527 7.22
ASC3 TV 0.000235 0.625 -7.29 0.000271 0.648 -6.93
ASC3 IN 0.00174 0.210 -7.67 0.00179 0.207 -7.32
CT TE 3.91e-005 0.0420 8.60 7.50e-005 0.0782 8.60
ASC3 PF 0.00175 0.210 -9.77 0.00170 0.195 -9.28
PK TE 2.02e-005 0.0644 10.57 1.75e-005 0.0555 10.39
PF TE -0.000268 -0.106 10.81 -0.000175 -0.0690 10.97
TE TV -7.83e-007 -0.00691 -11.39 1.09e-006 0.00896 -11.22
Smallest singular value of the hessian: 51.5862# mnl2 – segmentation:
segmentation of sharing or not sharing the car
- – and the frequency of assisting to college throughout the week.
// This file has automatically been generated.
// 05/20/25 16:18:39
// Michel Bierlaire, EPFL
biogeme 2.0 [Sat Oct 30 17:26:53 CEDT 2010]
Michel Bierlaire, EPFL
Modelo COCHE COMPARTIDO
Model: Multinomial Logit
Number of estimated parameters: 9
Number of observations: 1608
Number of individuals: 1608
Null log-likelihood: -1766.569
Cte log-likelihood: -1717.085
Init log-likelihood: -1766.569
Final log-likelihood: -1603.451
Likelihood ratio test: 326.235
Rho-square: 0.092
Adjusted rho-square: 0.087
Final gradient norm: +5.222e-003
Diagnostic: Convergence reached...
Iterations: 10
Run time: 00:00
Variance-covariance: from analytical hessian
Sample file: CARPOOL_24_25.dat
Utility parameters
******************
Name Value Std err t-test p-val Rob. std err Rob. t-test Rob. p-val
---- ----- ------- ------ ----- ------------ ----------- ----------
ASC1 0.00 --fixed--
ASC2 0.00 --fixed--
ASC3 -0.860 0.138 -6.22 0.00 0.143 -6.02 0.00
CT -0.0769 0.0228 -3.37 0.00 0.0233 -3.30 0.00
IN 0.0719 0.0603 1.19 0.23 * 0.0601 1.20 0.23 *
PF 0.364 0.0608 5.99 0.00 0.0605 6.03 0.00
PK -0.0304 0.00756 -4.03 0.00 0.00751 -4.06 0.00
TE -0.472 0.0415 -11.39 0.00 0.0422 -11.19 0.00
TE_FR2 0.729 0.241 3.02 0.00 0.242 3.02 0.00
TV -0.00177 0.00293 -0.60 0.55 * 0.00299 -0.59 0.55 *
TV_SOLO 0.692 0.142 4.87 0.00 0.137 5.06 0.00
Utility functions
*****************
3 NINGUNA AV3 ASC3 * one
1 OPCION1 AV1 ASC1 * one + CT * CTV1 + TV * T1 + PK * PK1 + TE * TE1 + PF * PF1 + IN * IN1 + TV_SOLO * T1_SOLO + TE_FR2 * T1_FR2
2 OPCION2 AV2 ASC2 * one + CT * CTV2 + TV * T2 + PK * PK2 + TE * TE2 + PF * PF2 + IN * IN2 + TV_SOLO * T2_SOLO + TE_FR2 * T2_FR2
Correlation of coefficients
***************************
Coeff1 Coeff2 Covariance Correlation t-test Rob. covar. Rob. correl. Rob. t-test
------ ------ ---------- ----------- ------ ----------- ------------ -----------
TE_FR2 TV_SOLO 0.00450 0.131 0.14 * 0.00382 0.116 0.14 *
IN TV -3.69e-007 -0.00209 1.22 * 7.84e-007 0.00437 1.22 *
PF TE_FR2 5.24e-005 0.00357 -1.47 * 7.27e-005 0.00498 -1.47 *
IN PK -2.01e-005 -0.0441 1.67 * -4.86e-006 -0.0108 1.69 *
CT PK -4.84e-006 -0.0280 -1.92 * -1.69e-006 -0.00969 -1.89 *
PF TV_SOLO 5.84e-005 0.00676 -2.12 4.58e-005 0.00554 -2.19
CT IN 2.09e-006 0.00152 -2.31 -3.11e-005 -0.0222 -2.29
IN TE_FR2 -5.10e-006 -0.000350 -2.64 -0.000109 -0.00749 -2.64
ASC3 TE 0.00118 0.206 -2.85 0.00141 0.234 -2.79
TE_FR2 TV 3.08e-005 0.0436 3.03 2.90e-005 0.0401 3.03
PK TE_FR2 6.73e-006 0.00369 -3.15 6.25e-006 0.00345 -3.14
CT TV -1.52e-005 -0.227 -3.18 -1.68e-005 -0.241 -3.11
CT TE_FR2 -0.000651 -0.118 -3.29 -0.000765 -0.136 -3.28
IN PF 0.000137 0.0374 -3.48 0.000306 0.0842 -3.59
PK TV 3.24e-007 0.0146 -3.55 -5.20e-007 -0.0232 -3.52
IN TV_SOLO 8.31e-006 0.000970 -4.02 0.000156 0.0190 -4.18
TV TV_SOLO -0.000137 -0.330 -4.85 -9.74e-005 -0.239 -5.05
TE TE_FR2 -9.72e-005 -0.00971 -4.90 -0.000248 -0.0243 -4.88
PK TV_SOLO -4.27e-006 -0.00398 -5.08 2.13e-005 0.0207 -5.28
CT TV_SOLO 7.81e-005 0.0241 -5.36 4.64e-005 0.0146 -5.56
ASC3 CT 0.000808 0.256 -5.83 0.000866 0.261 -5.65
PF TV -2.10e-006 -0.0118 6.01 -5.47e-006 -0.0303 6.04
ASC3 PK 0.000312 0.299 -6.09 0.000301 0.281 -5.89
ASC3 TE_FR2 0.00482 0.145 -6.11 0.00405 0.117 -5.98
ASC3 TV 0.000225 0.556 -6.28 0.000239 0.562 -6.08
PF PK -1.77e-005 -0.0386 6.42 -2.45e-005 -0.0539 6.44
ASC3 IN 0.00174 0.208 -6.71 0.00184 0.214 -6.54
CT PF -3.01e-005 -0.0217 -6.75 -5.31e-005 -0.0377 -6.73
IN TE -0.000104 -0.0414 7.29 -0.000119 -0.0471 7.25
TE TV_SOLO -2.64e-005 -0.00448 -7.86 0.000155 0.0269 -8.20
ASC3 TV_SOLO 0.00170 0.0867 -8.19 0.00289 0.148 -8.51
CT TE 4.25e-005 0.0449 8.52 8.49e-005 0.0864 8.52
ASC3 PF 0.00175 0.208 -8.81 0.00166 0.193 -8.51
PK TE 2.03e-005 0.0648 10.60 1.62e-005 0.0511 10.40
PF TE -0.000280 -0.111 10.82 -0.000194 -0.0758 10.96
TE TV -3.07e-007 -0.00252 -11.31 3.82e-007 0.00303 -11.12
Smallest singular value of the hessian: 16.83793# mnl3 – environmental bias
// This file has automatically been generated.
// 05/20/25 16:27:34
// Michel Bierlaire, EPFL
biogeme 2.0 [Sat Oct 30 17:26:53 CEDT 2010]
Michel Bierlaire, EPFL
Modelo COCHE COMPARTIDO
Model: Multinomial Logit
Number of estimated parameters: 10
Number of observations: 1608
Number of individuals: 1608
Null log-likelihood: -1766.569
Cte log-likelihood: -1717.085
Init log-likelihood: -1766.569
Final log-likelihood: -1595.976
Likelihood ratio test: 341.184
Rho-square: 0.097
Adjusted rho-square: 0.091
Final gradient norm: +5.676e-003
Diagnostic: Convergence reached...
Iterations: 11
Run time: 00:00
Variance-covariance: from analytical hessian
Sample file: CARPOOL_24_25_updated.dat
Utility parameters
******************
Name Value Std err t-test p-val Rob. std err Rob. t-test Rob. p-val
---- ----- ------- ------ ----- ------------ ----------- ----------
ASC1 0.00 --fixed--
ASC2 0.00 --fixed--
ASC3 -0.704 0.143 -4.91 0.00 0.147 -4.79 0.00
CT -0.0813 0.0229 -3.55 0.00 0.0234 -3.47 0.00
IN 0.0719 0.0604 1.19 0.23 * 0.0601 1.20 0.23 *
PF 0.365 0.0608 5.99 0.00 0.0605 6.03 0.00
PK -0.0304 0.00756 -4.02 0.00 0.00750 -4.05 0.00
PM -0.518 0.137 -3.78 0.00 0.138 -3.75 0.00
TE -0.472 0.0415 -11.38 0.00 0.0422 -11.18 0.00
TE_FR2 0.718 0.241 2.98 0.00 0.242 2.97 0.00
TV -0.00102 0.00295 -0.35 0.73 * 0.00300 -0.34 0.73 *
TV_SOLO 0.638 0.144 4.44 0.00 0.138 4.61 0.00
Utility functions
*****************
3 NINGUNA AV3 ASC3 * one + PM * CMED
1 OPCION1 AV1 ASC1 * one + CT * CTV1 + TV * T1 + PK * PK1 + TE * TE1 + PF * PF1 + IN * IN1 + TV_SOLO * T1_SOLO + TE_FR2 * T1_FR2
2 OPCION2 AV2 ASC2 * one + CT * CTV2 + TV * T2 + PK * PK2 + TE * TE2 + PF * PF2 + IN * IN2 + TV_SOLO * T2_SOLO + TE_FR2 * T2_FR2
Correlation of coefficients
***************************
Coeff1 Coeff2 Covariance Correlation t-test Rob. covar. Rob. correl. Rob. t-test
------ ------ ---------- ----------- ------ ----------- ------------ -----------
TE_FR2 TV_SOLO 0.00437 0.126 0.30 * 0.00349 0.104 0.30 *
PM TE 1.20e-005 0.00210 -0.32 * 0.000140 0.0240 -0.32 *
ASC3 PM -0.00513 -0.261 -0.83 * -0.00478 -0.235 -0.83 *
IN TV -4.04e-007 -0.00226 1.21 * 1.05e-006 0.00581 1.21 *
PF TE_FR2 5.20e-005 0.00354 -1.42 * 5.30e-005 0.00363 -1.42 *
ASC3 TE 0.00118 0.198 -1.64 * 0.00137 0.220 -1.61 *
IN PK -2.04e-005 -0.0446 1.67 * -3.79e-006 -0.00841 1.69 *
PF TV_SOLO 5.86e-005 0.00670 -1.76 * 7.65e-005 0.00914 -1.82 *
CT PK -4.82e-006 -0.0278 -2.09 -1.37e-006 -0.00781 -2.07
CT IN 2.52e-006 0.00182 -2.38 -3.17e-005 -0.0225 -2.36
IN TE_FR2 -5.84e-006 -0.000401 -2.60 -0.000104 -0.00715 -2.59
TE_FR2 TV 3.02e-005 0.0423 2.98 2.86e-005 0.0394 2.98
PK TE_FR2 6.33e-006 0.00347 -3.10 4.39e-006 0.00242 -3.10
CT PM 0.000161 0.0511 3.17 0.000341 0.105 3.17
CT TE_FR2 -0.000614 -0.111 -3.26 -0.000661 -0.117 -3.26
CT TV -1.58e-005 -0.233 -3.38 -1.78e-005 -0.253 -3.30
IN PF 0.000137 0.0374 -3.48 0.000306 0.0844 -3.59
PK PM -1.33e-006 -0.00128 3.55 7.25e-006 0.00699 3.52
IN TV_SOLO 8.64e-006 0.000996 -3.63 0.000142 0.0171 -3.78
PK TV 3.20e-007 0.0143 -3.63 -5.83e-007 -0.0259 -3.60
PM TV -2.51e-005 -0.0619 -3.77 -3.83e-005 -0.0922 -3.73
IN PM -3.98e-006 -0.000481 3.94 -3.34e-005 -0.00403 3.91
TV TV_SOLO -0.000147 -0.347 -4.42 -0.000110 -0.264 -4.59
ASC3 CT 0.000761 0.231 -4.45 0.000772 0.224 -4.34
PM TE_FR2 0.000190 0.00574 -4.46 -0.000393 -0.0118 -4.42
PK TV_SOLO -4.50e-006 -0.00414 -4.64 2.33e-005 0.0225 -4.83
ASC3 PK 0.000313 0.288 -4.76 0.000298 0.270 -4.64
TE TE_FR2 -9.89e-005 -0.00987 -4.85 -0.000241 -0.0236 -4.83
ASC3 TV 0.000233 0.551 -4.96 0.000249 0.565 -4.84
CT TV_SOLO 0.000110 0.0332 -4.97 0.000126 0.0389 -5.16
ASC3 IN 0.00174 0.201 -5.39 0.00186 0.210 -5.29
ASC3 TE_FR2 0.00484 0.140 -5.41 0.00436 0.123 -5.33
PF PM -1.08e-005 -0.00130 5.88 0.000115 0.0137 5.88
PF TV -2.06e-006 -0.0115 6.00 -5.95e-006 -0.0328 6.03
PM TV_SOLO 0.00165 0.0840 -6.08 0.00267 0.140 -6.37
PF PK -1.75e-005 -0.0380 6.41 -2.42e-005 -0.0533 6.44
ASC3 TV_SOLO 0.00111 0.0539 -6.80 0.00211 0.104 -7.02
CT PF -3.17e-005 -0.0227 -6.81 -5.40e-005 -0.0381 -6.79
IN TE -0.000104 -0.0416 7.29 -0.000120 -0.0471 7.25
ASC3 PF 0.00175 0.201 -7.42 0.00162 0.182 -7.20
TE TV_SOLO -2.42e-005 -0.00406 -7.42 0.000161 0.0276 -7.73
CT TE 4.50e-005 0.0473 8.42 9.05e-005 0.0915 8.43
PK TE 2.01e-005 0.0639 10.60 1.57e-005 0.0495 10.39
PF TE -0.000281 -0.111 10.82 -0.000196 -0.0767 10.96
TE TV -4.37e-007 -0.00357 -11.33 2.23e-007 0.00176 -11.13
Smallest singular value of the hessian: 16.8286