Returns the coefficients of the fitted market model.
Usage
# S4 method for market_fit
coef(object)
# S4 method for market_fit
coefficients(object)
Methods (by class)
coef(market_fit)
: Estimated coefficients.coefficients(market_fit)
: Estimated coefficients alias.
Examples
# \donttest{
# estimate a model using the houses dataset
fit <- diseq_deterministic_adjustment(
HS | RM | ID | TREND ~
RM + TREND + W + CSHS + L1RM + L2RM + MONTH |
RM + TREND + W + L1RM + MA6DSF + MA3DHF + MONTH,
fair_houses(),
correlated_shocks = FALSE,
estimation_options = list(control = list(maxit = 1e+6))
)
# access the estimated coefficients
coef(fit)
#> D_RM D_CONST D_TREND D_W D_CSHS
#> -6.39287048 -20.16533253 -3.09530903 2.77909898 0.02878931
#> D_L1RM D_L2RM D_MONTH02 D_MONTH03 D_MONTH04
#> 8.92812266 -2.48883659 17.94359360 28.55310947 78.00303909
#> D_MONTH05 D_MONTH06 D_MONTH07 D_MONTH08 D_MONTH09
#> 84.17025404 82.50861671 88.22174395 52.40940637 49.40057986
#> D_MONTH10 D_MONTH11 D_MONTH12 S_RM S_CONST
#> 67.05086057 24.50611800 30.86396923 0.46442865 -37.46456496
#> S_TREND S_W S_L1RM S_MA6DSF S_MA3DHF
#> -0.14554797 2.08578681 -0.40511192 0.04693627 0.03455421
#> S_MONTH02 S_MONTH03 S_MONTH04 S_MONTH05 S_MONTH06
#> 3.81910684 34.38727665 65.75523098 67.60421681 57.39161807
#> S_MONTH07 S_MONTH08 S_MONTH09 S_MONTH10 S_MONTH11
#> 43.90383859 49.34401811 44.93630427 49.43637822 32.80682646
#> S_MONTH12 RM_DIFF D_VARIANCE S_VARIANCE
#> 11.27185537 1.53371422 1295.13136810 107.76446554
coefficients(fit)
#> D_RM D_CONST D_TREND D_W D_CSHS
#> -6.39287048 -20.16533253 -3.09530903 2.77909898 0.02878931
#> D_L1RM D_L2RM D_MONTH02 D_MONTH03 D_MONTH04
#> 8.92812266 -2.48883659 17.94359360 28.55310947 78.00303909
#> D_MONTH05 D_MONTH06 D_MONTH07 D_MONTH08 D_MONTH09
#> 84.17025404 82.50861671 88.22174395 52.40940637 49.40057986
#> D_MONTH10 D_MONTH11 D_MONTH12 S_RM S_CONST
#> 67.05086057 24.50611800 30.86396923 0.46442865 -37.46456496
#> S_TREND S_W S_L1RM S_MA6DSF S_MA3DHF
#> -0.14554797 2.08578681 -0.40511192 0.04693627 0.03455421
#> S_MONTH02 S_MONTH03 S_MONTH04 S_MONTH05 S_MONTH06
#> 3.81910684 34.38727665 65.75523098 67.60421681 57.39161807
#> S_MONTH07 S_MONTH08 S_MONTH09 S_MONTH10 S_MONTH11
#> 43.90383859 49.34401811 44.93630427 49.43637822 32.80682646
#> S_MONTH12 RM_DIFF D_VARIANCE S_VARIANCE
#> 11.27185537 1.53371422 1295.13136810 107.76446554
# }