[Splm-commits] r169 - in pkg: R man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Jun 27 20:39:47 CEST 2013
Author: the_sculler
Date: 2013-06-27 20:39:47 +0200 (Thu, 27 Jun 2013)
New Revision: 169
Removed:
pkg/R/.Rapp.history
pkg/man/splm-package.Rd
Modified:
pkg/man/Insurance.Rd
pkg/man/RiceFarms.Rd
pkg/man/effects.splm.Rd
pkg/man/itaww.Rd
pkg/man/print.splm.Rd
pkg/man/riceww.Rd
pkg/man/spgm.Rd
pkg/man/sphtest.Rd
pkg/man/spml.Rd
pkg/man/spreml.Rd
pkg/man/summary.splm.Rd
pkg/man/usaww.Rd
pkg/man/write.effects.splm.Rd
Log:
Fixed pdf documentation
Deleted: pkg/R/.Rapp.history
===================================================================
--- pkg/R/.Rapp.history 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/R/.Rapp.history 2013-06-27 18:39:47 UTC (rev 169)
@@ -1,260 +0,0 @@
-install.packages("spatialprobit")
-library(spatialprobit)
-help(spatialprobit)
-install.packages("tmvtnorm")
-library(tmvtnorm)
-install.packages("mvtnorm")
-library(mvtnorm)
-library(Matrix)
-I_n_dense <- diag(10000)
-print(object.size(I_n_dense), units = "Mb")
-rm(I_n_dense)
-I_n_dense <- Diagonal(10000)
-print(object.size(I_n_dense), units = "Mb")
-I_n_dense
-rm(I_n_dense)
-I_n_dense <- sparseMatrix(i=1:10000, j =1:10000, x=1)
-I_n_dense
-print(object.size(I_n_dense), units = "Mb")
-rm(I_n_dense)
-I_n_dense <- Diagonal(10000)
-print(object.size(I_n_dense), units = "b")
-I_n_dense <- sparseMatrix(i=1:10000, j =1:10000, x=1)
-print(object.size(I_n_dense), units = "b")
-library(Matrix)
-I_n_dense <- diag(10000)
-print(object.size(I_n_dense), units = "b")
-print(object.size(I_n_dense), units = "Mb")
-rm(I_n_dense)
-I_n_dense <- sparseMatrix(i=1:10000, j =1:10000, x=1)
-print(object.size(I_n_dense), units = "Mb")
-print(object.size(I_n_dense), units = "b")
-rm(I_n_dense)
-I_n_dense <- Diagonal(10000)
-print(object.size(I_n_dense), units = "Mb")
-print(object.size(I_n_dense), units = "b")
-library(spatialprobit)
-n<- 400
-beta <- c(0, 1, -1)
-rho <- 0.75
-X <- cbind(intercept = 1, x = rnorm(n), y = rnorm(n))
-I_n <- sparseMatrix(i = 1:n, j = 1:n, x = 1)
-kNearestNeighbors
-W <- kNearestNeighbors(x = rnorm(n), y = rnorm(n), k = 6)
-W
-kNearestNeighbors
-knearneigh
-knearneighbours
-W <- kNearestNeighbors(x = 1:n, y =1:n, k = 6)
-help(kNearestNeighbors)
-library(spdep)
-eps <- rnorm(n = n, mean = 0, sd = 1)
-eps
-z <- solve(qr(I_n - rho * W), X %*% beta + eps)
-qr(I_n - rho * W)
-y <- as.vector(z >= 0)
-y
-sarprobit.fit1 <- sar_probit_mcmc(y, X, W, ndraw = 1000, burn.in = 200, thinning = 1, m = 10)
-summary(sarprobit.fit1)
-plot(sarprobit.fit1)
-library(igraph)
-install.packages("igraph")
-library(igraph)
-set.seed(1.2345)
-n <- 200
-branch <- 3
-probability <- branch/n
-probability
-grandom <- igraph::erdos.renyi.game(n = n, p.or.m = probability, type = "gnp", directed = F, loops = F)
-grandom
-V(grandom)$name <- 1:n
-A <- igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-A <- igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-A <- igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-A <- igraph::get.adjacency(grandom, type = "both", sparse = T)
-A
-W <- A/rowSums(A)
-plot(grandom, vertex.label.family = "sans", vertex.size = 2, vertex.label = "", layout = layout.fruchterman.reingold)
-x <- rnorm(n)
-X <- cbind(intercept = rep(1, n), x = x)
-p <- 0.3
-beta <- c(-1, 2)
-I_n <- sparseMatrix(i = 1:n, j = 1:n, x = 1)
-z <- solve(qr(I_n - p * W), X %*% beta + rnorm(n))
-y <- as.real(z >= 0)
-sarprobit.fit <- sar_probit_mcmc(y, X, W, ndraw = 3000, burn.in = 200, thinning = 1)
-y
-z <- solve(qr(I_n - p * W), X %*% beta + rnorm(n))
-z
-I_n <- sparseMatrix(i = 1:n, j = 1:n, x = 1)
-I_n
-x <- rnorm(n)#
-X <- cbind(intercept = rep(1, n), x = x)
-X
-p <- 0.3#
- beta <- c(-1, 2)#
- I_n <- sparseMatrix(i = 1:n, j = 1:n, x = 1)#
-z <- solve(qr(I_n - p * W), X %*% beta + rnorm(n))
-z
-qr(I_n - p * W)
-beta
-qr(I_n - p * W), X %*% beta
-solve(qr(I_n - p * W), X %*% beta + rnorm(n))
-x <- rnorm(n)
-x
-X <- cbind(intercept = rep(1, n), x = x)
-X
-p <- 0.3
-beta <- c(-1, 2)
-beta
-p <- 0.3
-I_n <- sparseMatrix(i = 1:n, j = 1:n, x = 1)
-solve(qr(I_n - p * W), X %*% beta + rnorm(n))
-W <- A/rowSums(A)
-W
-A <- igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-grandom
-V(grandom)$name <- 1:n
-igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-help(igraph::get.adjacency)
-W <- A/rowSums(A)
-W
-grandom <- igraph::erdos.renyi.game(n = n, p.or.m = probability, type = "gnp", directed = F, loops = F)
-grandom
-V(grandom)$name <- 1:n
-A <- igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-load("CMK.RData")
-library(igraph)#
-set.seed(1.2345)#
-n <- 200#
-branch <- 3#
-probability <- branch/n#
-grandom <- igraph::erdos.renyi.game(n = n, p.or.m = probability, type = "gnp", directed = F, loops = F)#
-V(grandom)$name <- 1:n
-A <- igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-W <- A/rowSums(A)
-A <- igraph::get.adjacency(grandom, type = "both", binary = T, sparse = T)
-W <- A/rowSums(A)
-t = 2
-T=2
-IT<- diag(T)
-IT
-N=3
-IN <- diag(N)
-IN
-JT<- matrix(1,2,2)
-JT
-Jbar<- 1/T*JT
-Jbar
-Q=IT-Jbar;
-Q
-Q=IT-Jbar
-Q
-eigen(Q)
-vec<-eigen(Q)
-vec
-vec$vectors[vec$vectors==1]
-vec$vectors[vec$vectors==1,]
-vec$vectors[vec$values==1]
-vec$vectors[,vec$values==1]
-kroneker(vec$vectors[,vec$values==1] , IN)
-kronecker(vec$vectors[,vec$values==1] , IN)
-kronecker(t(vec$vectors[,vec$values==1] ), IN)
-vec$vectors[vec$values==1]
-vec$vectors[vec$values==1]
-vec$vectors[vec$vectors==1,]
-vec$vectors[vec$values==1,]
-kronecker(t(vec$vectors[,vec$values==1] ), IN)
-Fmat <- vec$vectors[,vec$values==1]
-Fmat
-kronecker(t(Fmat), IN)
-Ftm <- kronecker(t(Fmat), IN)
-Ftm
-IT <- Diagonal(T)
-IT <- Diagonal(T)
-IT <- Diag(T)
-library(Matrix)
-IT <- Diag(T)
-IT <- Diag(T)
-IT <- Diagonal(T)
-IT
-IN <- diag(n)
-IN <- Diagonal(n)
-n=N
-IN <- Diagonal(n)
-IN
-JT <- matrix(1,T,T)
-JT
-Jbar <- 1/T * JT
-Jbar
-Qmat <-IT - Jbar
-Qmat
-vec <- eigen(Qmat)
-vec
-Fmat <- vec$vectors[,vec$values==1]
-Fmat
-Ftm <- kronecker(t(Fmat), IN)
-Ftm
-Fmat <- vec$vectors[,vec$values==L1]
-Fmat <- vec$vectors[,vec$values==1L]
-Fmat
-Ftm <- kronecker(t(Fmat), IN)
-Ftm
-iotan <- matrix(1,1,n)
-iotan
-iotan <- matrix(1,n,1)
-iotan
-Jnbar <-1/n * iotan %*% t(iotan)
-Jnbar
-Qmat1 <- IN - Jnbar
-Qmat1
-vec1 <- eigen(Qmat1)
-vec1
-Fmat1 <- vec1$vectors[,vec1$values==1L]
-Fmat1
-FFmat<- kronecker(t(Fmat), t(Fmat1))
-FFmat
-FFmat<- kronecker(Fmat, Fmat1)
-FFmat
-Fmat
-Fmat1
-Fmat1
-Fmat
-Fmat <- matrix(vec$vectors[,vec$values==1L], T, T-1)
-Fmat
-Ftm <- kronecker(t(Fmat), IN)
-Ftm
-Fmat1 <- matrix(vec1$vectors[,vec1$values==1L], n, n-1)
-Fmat1
-FFmat<- kronecker(Fmat, Fmat1)
-FFmat
-FFmat<- kronecker(t(Fmat), Fmat1)
-FFmat
-Ftm
-FFmat<- kronecker(t(Fmat), Fmat1)
-FFmat
-FFmat<- kronecker(Fmat, Fmat1)
-FFmat
-FFmat<- kronecker(Fmat, t(Fmat1))
-FFmat
-FFmat<- kronecker(t(Fmat), t(Fmat1))
-FFmat
-help(spfeml)
-help(spml)
-help(spfeml)
-help(spml)
-help(splm)
-help(spml)
-library(splm)
-help(spfeml)
-library(splm)
-help(spml)
-help(spgm)
-library(spdep)
-library(spdep)
-help(sacsarlm)
-sacsarlm
-help(sarlm)
-lagsarlm
-help(lagsarlm)
-errorsarlm
Modified: pkg/man/Insurance.Rd
===================================================================
--- pkg/man/Insurance.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/Insurance.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -3,7 +3,7 @@
\alias{Insurance}
\title{Insurance consumption across Italian provinces, 1998-2002}
\description{
- a panel of 103 observations
+ A panel of 103 observations
\emph{number of observations} : 515
Modified: pkg/man/RiceFarms.Rd
===================================================================
--- pkg/man/RiceFarms.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/RiceFarms.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -3,7 +3,7 @@
\alias{RiceFarms}
\title{Production of Rice in Indonesia}
\description{
- a panel of 171 observations
+ A panel of 171 observations
\emph{number of observations} : 1026
Modified: pkg/man/effects.splm.Rd
===================================================================
--- pkg/man/effects.splm.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/effects.splm.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -55,11 +55,7 @@
data(Produc, package = "Ecdat")
data(usaww)
fm <- log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp
-#lag <- spml(fm, data = Produc, listw = mat2listw(usaww), model="within", effect="twoways", lag=TRUE, method="eigen", Hess = TRUE)
-#summary(lag)
-#eff <- effects(lag)
-#print(eff)
-err <- spml(fm, data = Produc, listw = mat2listw(usaww), model="within", effect="time", spatial.error="b", method="eigen", Hess = FALSE)
+err <- spml(fm, data = Produc, listw = mat2listw(usaww), model="within")
summary(err)
eff <- effects(err)
print(eff)
Modified: pkg/man/itaww.Rd
===================================================================
--- pkg/man/itaww.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/itaww.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -9,7 +9,7 @@
}
\usage{
-usaww
+data(itaww)
}
\format{
Modified: pkg/man/print.splm.Rd
===================================================================
--- pkg/man/print.splm.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/print.splm.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -30,7 +30,7 @@
\seealso{
\code{\link{spml}}, \code{\link{spgm}}
}
-\author{ Giovanni Millo \email{Giovanni\_Millo at Generali.com}, Gianfranco Piras\email{gpiras at mac.com}}
+\author{Giovanni Millo, Gianfranco Piras}
\examples{
data(Produc, package = "Ecdat")
Modified: pkg/man/riceww.Rd
===================================================================
--- pkg/man/riceww.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/riceww.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -9,7 +9,7 @@
}
\usage{
-usaww
+data(riceww)
}
\format{
Modified: pkg/man/spgm.Rd
===================================================================
--- pkg/man/spgm.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/spgm.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -21,10 +21,10 @@
\usage{
spgm(formula, data=list(), index=NULL, listw,
- model=c("within","random"), lag=FALSE, spatial.error=FALSE,
- moments = c("initial", "weights", "fullweights"), endog = NULL,
- instruments= NULL, verbose = FALSE,
- method = c("w2sls", "b2sls", "g2sls", "ec2sls"), control = list())
+ model=c("within","random"), lag=FALSE, spatial.error=FALSE,
+ moments = c("initial", "weights", "fullweights"), endog = NULL,
+ instruments= NULL, verbose = FALSE,
+ method = c("w2sls", "b2sls", "g2sls", "ec2sls"), control = list())
}
\arguments{
@@ -138,7 +138,8 @@
\examples{
data(Produc, package = "Ecdat")
data(usaww)
-GM<-spgm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc,listw = usaww, moments="fullweights", spatial.error = TRUE)
+GM <- spgm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc,
+ listw = usaww, moments="fullweights", spatial.error = TRUE)
summary(GM)
}
Modified: pkg/man/sphtest.Rd
===================================================================
--- pkg/man/sphtest.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/sphtest.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -9,7 +9,9 @@
}
\usage{
sphtest(x, ...)
-\method{sphtest}{formula}(x, data, index = NULL, listw, spatial.model = c("lag", "error", "sarar"), method = c("ML", "GM"), errors = c("KKP", "BSK"),...)
+\method{sphtest}{formula}(x, data, index = NULL, listw,
+ spatial.model = c("lag", "error", "sarar"),
+ method = c("ML", "GM"), errors = c("KKP", "BSK"),...)
\method{sphtest}{splm}(x, x2, ...)
}
@@ -44,10 +46,13 @@
data(Produc, package="Ecdat")
data(usaww)
fm <- log(gsp)~log(pcap)+log(pc)+log(emp)+unemp
-test1<-sphtest(fm,data=Produc, listw = mat2listw(usaww), spatial.model = "error", method="GM")
+test1<-sphtest(fm,data=Produc, listw = mat2listw(usaww),
+ spatial.model = "error", method="GM")
test1
-mod1<- spgm(fm, data=Produc, listw = usaww, model = "random", spatial.error = TRUE, moments="fullweights")
-mod2<- spgm(fm, data=Produc, listw = usaww, model = "within", spatial.error = TRUE)
+mod1<- spgm(fm, data=Produc, listw = usaww, model = "random",
+ spatial.error = TRUE, moments="fullweights")
+mod2<- spgm(fm, data=Produc, listw = usaww, model = "within",
+ spatial.error = TRUE)
test2<-sphtest(mod1, mod2)
test2
}
Deleted: pkg/man/splm-package.Rd
===================================================================
--- pkg/man/splm-package.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/splm-package.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -1,88 +0,0 @@
-\name{splm-package}
-\alias{splm-package}
-\alias{splm}
-\docType{package}
-\title{
-Spatial panel models: estimation and testing
-}
-\description{
-A comprehensive toolset for ML and GM estimation and diagnostic testing of econometric models for spatial panel data.
-}
-\details{
-\tabular{ll}{
-Package: \tab splm\cr
-Type: \tab Package\cr
-Version: \tab 0.2-1\cr
-Date: \tab 2010-06-08\cr
-License: \tab GPL\cr
-LazyLoad: \tab yes\cr
-}
-}
-
-\author{
-Giovanni Millo and Gianfranco Piras
-
-Maintainer: Giovanni Millo <giovanni\_millo at generali.com>
-}
-
-\references{
-Anselin, L. and Le Gallo, J. and Jayet, H. (2008)
-Spatial Panel Econometrics, \emph{In}
-Matyas, L. and Sevestre, P. (eds), \emph{The econometrics of Panel
-Data, Fundamentals and Recent Developments in Theory and Practice (3rd
-Edition)}, pages 624--660. Springer-Verlag, Berlin Heidelberg.
-
-Baltagi, B.H., Song, S.H., Jung B. and Koh, W. (2007)
-Testing panel data regression models with spatial and serial error correlation.
-\emph{Journal of Econometrics}, \bold{140}, 5-51.
-
-Baltagi, B.H., Song, S.H. and Koh, W. (2003)
-Testing panel data regression models with spatial error correlation.
-\emph{Journal of Econometrics}, \bold{117}, 123--150.
-
- Elhorst, J.P. (2003)
-Specification and estimation of spatial panel data models,
- \emph{International Regional Science Review}, \bold{26}, pages 244--268.
-
- Elhorst, J.P. (2009)
-Spatial panel data models,
- \emph{In} Fischer, M.M. and Getis, A. (eds),
- \emph{Handbook of Applied Spatial Analysis} Springer, Berlin.
-
- Kapoor, M., Kelejian, H.H. and Prucha, I.R. (2007)
- Panel data model with spatially correlated error components,
- \emph{Journal of Econometrics}, \bold{140}, pages 97--130.
-
- Kelejian, H.H. and Prucha, I.R. (1999)
-A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model,
- \emph{International Economic Review}, \bold{40}, pages 509--533.
-
- Kelejian, H.H. and Prucha, I.R. (1999)
-A Generalized Spatial Two Stage Least Square Procedure for Estimating a Spatial Autoregressive
-Model with Autoregressive Disturbances,
- \emph{Journal of Real Estate Finance and Economics}, \bold{17}, pages 99--121.
-
- Kelejian, H.H. and Prucha, I.R. (2004)
-Estimation of Simultaneous systems of spatially interrelated cross sectional equations,
-\emph{Journal of Econometrics}, \bold{118}, pages 27--50.
-
-Millo, G., Piras, G. (2012)
-splm: Spatial Panel Data Models in R.
-\emph{Journal of Statistical Software}, \bold{47(1)}, 1--38.
-URL http://www.jstatsoft.org/v47/i01/.
-}
-
-
-\keyword{ package }
-
-\examples{
-data(Produc, package = "Ecdat")
-data(usaww)
-Produc <- Produc[Produc$year<1975, ]
-fm <- log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp
-GM<-spgm(log(gsp)~log(pcap)+log(pc)+log(emp) + unemp, data = Produc, listw = usaww, moments = "fullweights", spatial.error = TRUE)
-summary(GM)
-respaterr <- spml(fm, data = Produc, listw = mat2listw(usaww), model="random", spatial.error="b")
-summary(respaterr)
-
-}
Modified: pkg/man/spml.Rd
===================================================================
--- pkg/man/spml.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/spml.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -87,10 +87,12 @@
## the two standard specifications (SEM and SAR) one with FE
## and the other with RE:
## fixed effects panel with spatial errors
-fespaterr <- spml(fm, data = Produc, listw = mat2listw(usaww), model="within", spatial.error="b", Hess = FALSE)
+fespaterr <- spml(fm, data = Produc, listw = mat2listw(usaww),
+ model="within", spatial.error="b", Hess = FALSE)
summary(fespaterr)
## random effects panel with spatial lag
-respatlag <- spml(fm, data = Produc, listw = mat2listw(usaww), model="random", spatial.error="none", lag=TRUE)
+respatlag <- spml(fm, data = Produc, listw = mat2listw(usaww),
+ model="random", spatial.error="none", lag=TRUE)
summary(respatlag)
}
Modified: pkg/man/spreml.Rd
===================================================================
--- pkg/man/spreml.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/spreml.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -21,7 +21,7 @@
\item{index}{if not NULL (default), a character vector to identify the indexes among the columns of the \code{\link{data.frame}}}
\item{w}{an object of class \code{listw} or a \code{matrix}. It represents the spatial weights to be used in estimation.}
\item{w2}{an object of class \code{listw} or a
- \code{matrix}. Second of set spatial weights for estimation, if
+ \code{matrix}. Second set of spatial weights for estimation, if
different from the first (e.g., in a 'sarar' model).}
\item{lag}{default=\code{FALSE}. If \code{TRUE}, a spatial lag of the dependent variable is added.}
\item{errors}{Specifies the error covariance structure. See details.}
@@ -48,7 +48,7 @@
Abbreviations in \code{errors} correspond to: \code{"sem"}
Anselin-Baltagi type spatial autoregressive error: if
present, random effects are not spatially correlated; \code{"sem2"}
- Kapoor, Kelejin and Prucha-type spatial autoregressive error model
+ Kapoor, Kelejian and Prucha-type spatial autoregressive error model
with spatially correlated random effects; \code{"sr"} serially
correlated remainder errors; \code{"re"} random effects; \code{"ols"}
spherical errors (usually combined with \code{lag=T}).
@@ -80,8 +80,8 @@
\references{
Millo, G. (2013)
Maximum likelihood estimation of spatially and serially correlated
- panels with random effects. Submitted to \emph{Computational
- Statistics and Data Analysis}.
+ panels with random effects. \emph{Computational Statistics and Data
+ Analysis}, \bold{forthcoming}.
}
\author{Giovanni Millo}
@@ -94,7 +94,8 @@
fm <- log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp
## random effects panel with spatial lag and serial error correlation
## optimization method set to "BFGS"
-sarsrmod <- spreml(fm, data = Produc, w = usaww, errors="sr", lag=TRUE, method="BFGS")
+sarsrmod <- spreml(fm, data = Produc, w = usaww, errors="sr", lag=TRUE,
+ method="BFGS")
summary(sarsrmod)
}
Modified: pkg/man/summary.splm.Rd
===================================================================
--- pkg/man/summary.splm.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/summary.splm.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -45,7 +45,8 @@
\examples{
data(Produc, package = "Ecdat")
data(usaww)
-GM<-spgm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc, listw = usaww, moments = "fullweights", spatial.error = TRUE)
+GM <- spgm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc,
+ listw=usaww, moments = "fullweights", spatial.error = TRUE)
summary(GM)
}
Modified: pkg/man/usaww.Rd
===================================================================
--- pkg/man/usaww.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/usaww.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -9,7 +9,7 @@
}
\usage{
-usaww
+data(usaww)
}
\format{
Modified: pkg/man/write.effects.splm.Rd
===================================================================
--- pkg/man/write.effects.splm.Rd 2013-05-27 10:20:39 UTC (rev 168)
+++ pkg/man/write.effects.splm.Rd 2013-06-27 18:39:47 UTC (rev 169)
@@ -47,11 +47,8 @@
data(Produc, package = "Ecdat")
data(usaww)
fm <- log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp
-#lag <- spml(fm, data = Produc, listw = mat2listw(usaww), model="within", effect="twoways", lag=TRUE, method="eigen")
-#summary(lag)
-#eff <- effects(lag)
-#print(eff)
-err <- spml(fm, data = Produc, listw = mat2listw(usaww), model="within", effect="time", spatial.error="b", method="eigen", Hess= FALSE)
+err <- spml(fm, data = Produc, listw = mat2listw(usaww), model="within",
+ effect="time", spatial.error="b", method="eigen", Hess= FALSE)
summary(err)
eff <- effects(err)
write.effects.splm(eff)
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