A SpatialPointsDataFrame containing a sample of 50 apartaments with prices and other attributes in Florianopolis' downtown
zilli_2020
A tibble with 53 rows (50 samples and 3 apartments to be appraised) and 7 variables:
VT: price, in brazilian Reais
VU: price per sq. meter
AP: Private Area, in squared meters
DPXV: Distance to Praça XV
DSBM: Distance to Beira Mar Mall
DSIG: Distance to Iguatemi Mall
DCTC: Distance to CTC/UFSC
DABM: Distance to Beira Mar Avenue
ND: Number of rooms
NB: Number of bathrooms
NS: Number of ensuites
NG: Number of garages
MO: Furnishes - N (none), SM (some), MO (full)
PSN: Swimming pool?
CH: Barbecue grill?
PC: Building Standard - B, M, A (i.e. low, normal, high)
BRO: Neighborhood
ZILLI, Carlos Augusto. Regressão geograficamente ponderada aplicada na avaliação em massa de imóveis urbanos.. 2020. Dissertação de Mestrado em Engenharia de Transportes e Gestão Territorial. Centro Tecnológico da UFSC. Florianópolis/SC.
data(zilli_2020) zilli_2020$PC <- as.numeric(zilli_2020$PC) fit <- lm(log(VU) ~ log(AP) + log(DABM) + ND + NB + NG + PSN + PC, data = zilli_2020[1:190, ], subset = -c(86, 115)) summary(fit)#> #> Call: #> lm(formula = log(VU) ~ log(AP) + log(DABM) + ND + NB + NG + PSN + #> PC, data = zilli_2020[1:190, ], subset = -c(86, 115)) #> #> Residuals: #> Min 1Q Median 3Q Max #> -0.35287 -0.11336 -0.00861 0.12433 0.32240 #> #> Coefficients: #> Estimate Std. Error t value Pr(>|t|) #> (Intercept) 10.43675 0.27067 38.559 < 2e-16 *** #> log(AP) -0.41226 0.05842 -7.056 3.56e-11 *** #> log(DABM) -0.10276 0.01537 -6.688 2.76e-10 *** #> ND 0.06686 0.02285 2.926 0.003870 ** #> NB 0.04478 0.01802 2.486 0.013841 * #> NG 0.17503 0.02251 7.775 5.62e-13 *** #> PSN 0.09764 0.02788 3.502 0.000582 *** #> PC 0.20016 0.01792 11.171 < 2e-16 *** #> --- #> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 #> #> Residual standard error: 0.1538 on 180 degrees of freedom #> Multiple R-squared: 0.7959, Adjusted R-squared: 0.7879 #> F-statistic: 100.3 on 7 and 180 DF, p-value: < 2.2e-16 #>fefit <- lm(log(VU) ~ log(AP) + log(DABM) + ND + NB + NG + PSN + PC + BRO, data = zilli_2020[1:190, ], subset = -c(86, 115)) summary(fefit)#> #> Call: #> lm(formula = log(VU) ~ log(AP) + log(DABM) + ND + NB + NG + PSN + #> PC + BRO, data = zilli_2020[1:190, ], subset = -c(86, 115)) #> #> Residuals: #> Min 1Q Median 3Q Max #> -0.30800 -0.10457 -0.00621 0.09433 0.38946 #> #> Coefficients: #> Estimate Std. Error t value Pr(>|t|) #> (Intercept) 10.48055 0.25862 40.525 < 2e-16 *** #> log(AP) -0.41074 0.05510 -7.454 3.80e-12 *** #> log(DABM) -0.10028 0.01758 -5.703 4.81e-08 *** #> ND 0.06671 0.02152 3.100 0.002247 ** #> NB 0.03626 0.01706 2.126 0.034909 * #> NG 0.17415 0.02126 8.191 4.88e-14 *** #> PSN 0.09969 0.02690 3.706 0.000281 *** #> PC 0.20571 0.01693 12.149 < 2e-16 *** #> BROAgronomica -0.10746 0.03072 -3.498 0.000593 *** #> BROTrindade -0.10758 0.02941 -3.657 0.000336 *** #> --- #> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 #> #> Residual standard error: 0.1448 on 178 degrees of freedom #> Multiple R-squared: 0.8211, Adjusted R-squared: 0.8121 #> F-statistic: 90.78 on 9 and 178 DF, p-value: < 2.2e-16 #>