loteamento: Land division data

In lfpdroubi/appraiseR: R Package For Real Estate Appraisals

Land division data

Description

A tibble containing a sample of 20 plots in subdivision in Florianopolis. Paradigm situation: dry, flat, 15m front width and 30~60m length.

Usage

loteamento

Format

A tibble with 20 rows and 8 variables:

• valor: price, in brazilian Reais

• area: land area in squared meters

• tipo: type: offer or sale - venda, oferta (i.e. sale, offer)

• frente: front width of the land in meters

• profundidade: length of the land in meters

• topo: topography - plano, aclive (i.e. flat, slope)

• inclinacao: slope

• pedologia: pedology - seco, pantanoso (i.e. dry, marshy)

Source

HOCHHEIM, Norberto. Engenharia de Avaliacoes I. Florianopolis: IBAPE/SC, 2005, p.74

Examples

data(loteamento)

# Fatores do IBAPE/SP 2005 (aditivo), cf. Hochheim (2005 , p.82)
loteamento <- within(loteamento, {
               Coferta <- ifelse(tipo == "oferta", 1.11, 1)
               Cfrente <- (frente/15)^0.15
               Ctopo <- ifelse(topo == "plano", 1,
                          ifelse(inclinacao/100 >= .20, 0.85,
                            ifelse(inclinacao/100 > .10,  0.90,
                              ifelse(inclinacao/100 > 0, .95,
                                ifelse(inclinacao/100 >= -.05, .95,
                                  ifelse(inclinacao/100 >= -.10, .9,
                                    ifelse(inclinacao/100 >= -.20, .80, .70)))))))
               Cpedo <- ifelse(pedologia == "seco", 1, .6)
               Chom <-  (1 + ((Coferta - 1) + (Cfrente - 1) +
                                      (Ctopo - 1) + (Cpedo - 1)))
               PU <- valor/area
               PUhom <- PU/Chom
}
)

# Saneamento da amostra
outlier_analysis(loteamento$PUhom)
outlier_analysis(loteamento$PUhom, "2_sd")
outlier_analysis(loteamento$PUhom, "chauvenet")

# Avaliacao final
PUmedio <- mean(loteamento$PUhom[-c(7, 19)])
sdPU <- sd(loteamento$PUhom[-c(7, 19)])

# Poder de predicao
loteamento <- within(loteamento, P <- PUmedio*area*Chom)
powerPlot(y = loteamento$valor[-c(7, 19)], yhat = loteamento$P[-c(7, 19)],
           axis = "inverted")

# Fatores IBAPE/SP 2011 (misto)

loteamento <- within(loteamento, {
               Coferta <- ifelse(tipo == "oferta", 1.11, 1)
               Cfrente <- (frente/15)^0.15
               Ctopo <- ifelse(topo == "plano", 1,
                          ifelse(inclinacao/100 >= .20, 0.85,
                            ifelse(inclinacao/100 > .10,  0.90,
                              ifelse(inclinacao/100 > 0, .95,
                                ifelse(inclinacao/100 >= -.05, .95,
                                  ifelse(inclinacao/100 >= -.10, .9,
                                    ifelse(inclinacao/100 >= -.20, .80, .70)))))))
               Cpedo <- ifelse(pedologia == "seco", 1, .6)
               Chom <-  Coferta*(1 + ((Cfrente - 1) + (Ctopo - 1) +
                                  (Cpedo - 1)))
               PU <- valor/area
               PUhom <- PU/Chom
}
)

# Saneamento da amostra
outlier_analysis(loteamento$PUhom)
outlier_analysis(loteamento$PUhom, "2_sd")
outlier_analysis(loteamento$PUhom, "chauvenet")

# Avaliacao final
PUmedio <- mean(loteamento$PUhom[-c(7, 19)])
sdPU <- sd(loteamento$PUhom[-c(7, 19)])

# Poder de predicao
loteamento <- within(loteamento, P <- PUmedio*area*Chom)
powerPlot(y = loteamento$valor[-c(7, 19)], yhat = loteamento$P[-c(7, 19)],
           axis = "inverted")

# Fatores multiplicativos
loteamento <- within(loteamento, {
               Coferta <- ifelse(tipo == "oferta", 1.11, 1)
               Cfrente <- (frente/15)^0.25
               Chom <-  Coferta*Cfrente*Ctopo*Cpedo
               PU <- valor/area
               PUhom <- PU/Chom
}
)

# Saneamento da amostra
outlier_analysis(loteamento$PUhom)
outlier_analysis(loteamento$PUhom, "2_sd")
outlier_analysis(loteamento$PUhom, "chauvenet")

# Avaliacao final
PUmedio <- mean(loteamento$PUhom[-c(7, 19)])
sdPU <- sd(loteamento$PUhom[-c(7, 19)])

# Poder de predicao
loteamento <- within(loteamento, P <- PUmedio*area*Chom)
powerPlot(y = loteamento$valor[-c(7, 19)], yhat = loteamento$P[-c(7, 19)],
           axis = "inverted")

# Regressao Linear
fit <- lm(log(PU) ~ log(frente/15) + tipo + poly(inclinacao, 2) + pedologia,
           data = loteamento, subset = -c(7, 19))
powerPlot(fit, axis = "inverted", scale = "original", func = "log")
p <- predict(fit, newdata = list(frente = 15, tipo = "venda", inclinacao = 0,
                              pedologia = "seco"))
exp(p)

lfpdroubi/appraiseR documentation built on April 14, 2024, 10:27 p.m.