impacts.ols_sphet {sphet} | R Documentation |
Generate impacts for objects of class ols_sphet created in sphet
Description
Generate impacts for objects of class ols_sphet created in sphet
Usage
## S3 method for class 'ols_sphet'
impacts(
obj,
...,
tr = NULL,
R = NULL,
listw = NULL,
evalues = NULL,
tol = 1e-06,
empirical = FALSE,
Q = NULL
)
Arguments
obj |
A spreg spatial regression object created by |
... |
Arguments passed through to methods in the coda package |
tr |
A vector of traces of powers of the spatial weights matrix created using |
R |
If given, simulations are used to compute distributions for the impact measures, returned as |
listw |
a listw object |
evalues |
vector of eigenvalues of spatial weights matrix for impacts calculations |
tol |
Argument passed to |
empirical |
Argument passed to |
Q |
default NULL, else an integer number of cumulative power series impacts to calculate if |
Value
Estimate of the Average Total, Average Direct, and Average Indirect Effects
Examples
data(boston, package="spData")
Wb <- as(spdep::nb2listw(boston.soi), "CsparseMatrix")
ev <- eigen(Wb)$values
trMatb <- spatialreg::trW(Wb, type="mult")
lm.D <- spreg(log(CMEDV) ~ CRIM + ZN + INDUS + CHAS + I(NOX^2) + I(RM^2) + AGE + log(DIS),
data = boston.c, listw = Wb, model = "ols", Durbin = TRUE)
summary(lm.D)
impacts(lm.D)
summary(impacts(lm.D))
lm.D2 <- spreg(log(CMEDV) ~ CRIM + ZN + INDUS + CHAS + I(NOX^2) + I(RM^2) + AGE + log(DIS),
data = boston.c, listw = Wb, model = "ols", Durbin = ~AGE)
summary(lm.D2)
impacts(lm.D2)
summary(impacts(lm.D2))
lm.D3 <- spreg(log(CMEDV) ~ CRIM + ZN + CHAS + I(NOX^2) + I(RM^2) + AGE,
data = boston.c, listw = Wb, model = "ols", Durbin = ~AGE + INDUS )
summary(lm.D3)
impacts(lm.D3)
summary(impacts(lm.D3))
require("sf", quietly=TRUE)
columbus <- st_read(system.file("shapes/columbus.shp", package="spData")[1], quiet=TRUE)
col.gal.nb <- spdep::read.gal(system.file("weights/columbus.gal", package="spData")[1])
listw <- spdep::nb2listw(col.gal.nb)
knear <- spdep::knearneigh(cbind(columbus$X, columbus$Y), 5)
knb <- spdep::knn2nb(knear)
dist <- spdep::nbdists(knb, cbind(columbus$X, columbus$Y))
k5d <- spdep::nb2listw(knb, glist = dist, style = "B")
class(k5d) <- c("listw", "nb", "distance")
lm.D4 <- spreg(CRIME ~ INC + HOVAL, columbus, listw, Durbin=TRUE,
model = "ols")
summary(lm.D4)
impacts(lm.D4)
lm.D5 <- spreg(CRIME ~ INC + HOVAL, columbus, listw, Durbin= ~ INC,
model = "ols")
summary(lm.D5)
impacts(lm.D5)
summary(impacts(lm.D5))
lm.D6 <- spreg(CRIME ~ HOVAL, columbus, listw, Durbin= ~ INC,
model = "ols")
summary(lm.D6)
summary(impacts(lm.D6))
## Not run:
lm.D7 <- spreg(CRIME ~ INC + HOVAL, columbus, listw,
model = "ols", HAC = TRUE, distance = k5d,
type = "Triangular")
summary(lm.D7)
impacts(lm.D7)
summary(impacts(lm.D7))
## End(Not run)
lm.D8 <- spreg(CRIME ~ INC + HOVAL, data = columbus, listw = listw, Durbin=TRUE,
model = "ols", distance = k5d, type = "Triangular")
summary(lm.D8)
impacts(lm.D8)
summary(impacts(lm.D8))
lmD.9 <- spreg(CRIME ~ INC + HOVAL, data = columbus, listw = listw, Durbin= ~ INC,
model = "ols", distance = k5d, type = "Parzen")
impacts(lmD.9)
lmD.10 <- spreg(CRIME ~ HOVAL, columbus, listw, Durbin= ~ INC,
model = "ols", distance = k5d, type = "Bisquare")
summary(lmD.10)
summary(impacts(lmD.10))