"Abridged" description of SpatialPolygonsDataFrame objects?

If "d" is a SPolyDF

## first row/object
d[1,]
str(d[1,])

## the first Polygons object itself  (Polygons can be of many)
d at polygons[[1]]
str(d at polygons[[1]])

## the first Polygon in the first Polygons object
d at polygons[[1]]@Polygons[[1]]
str(d at polygons[[1]]@Polygons[[1]])

Another possibility is to use the arguments to str(), in particular, 
setting max.level=2 prevents str() going into deeper levels of the nested 
object. Judicious use of slot() in str(), with the max.level= gives a good 
degree of control.

Roger

Agustin Lobo wrote:
Hi!

If I do str(a) where a is a SpatialGridDataFrame, I get
a description of the structure that is readable,
but for SpatialPolygonsDataFrame the output of str() is
too long. Is there any way of looking at the
structure of a SpatialPolygonsDataFrame object just down to
a certain level? For example, not getting the structure of the
each polygon but getting the first one only.

Thanks
Agus

_______________________________________________
R-sig-Geo mailing list
R-sig-Geo at stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/r-sig-geo

Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no
List,

I would like to grab the standard errors of the regression parameters from an
spautolm object.  Currently I am using...

mod1 <- spautolm(y~var1 + var2,....)

mod1_sd <-  (diag(mod1$fit[["imat"]])^2

This does produce a vector of the diagonal elements of a matrix that look like a
 variance covariance matrix (correct dimensions and row and column labels), but
the values I get do not agree with what the summary() function displays -- they
also seem implausibly small. 

any hints?

Thanks!

Sam
********Note the new contact information*******

Samuel H. Field, Ph.D. 
Senior Research Investigator
CHERP/Division of Internal Medicine - University of Pennsylvania
Philadelphia VA Medical Center
3900 Woodland Ave (9 East)
Philadelphia, PA 19104
(215) 823-5800 EXT. 6155 (Office)
(215) 823-6330 (Fax)

List,

I would like to grab the standard errors of the regression parameters from an
spautolm object.  Currently I am using...

mod1 <- spautolm(y~var1 + var2,....)

mod1_sd <-  (diag(mod1$fit[["imat"]])^2
As with most model fitting functions, you use the summary method, so

summary(mod1)$Coef

is a four-column matrix, and

summary(mod1)$Coef[,2]

is the column you want.

Roger

PS. Reading summary.spautolm shows that the diagonal values of the matrix 
you refer to are the squares of the SE values.

This does produce a vector of the diagonal elements of a matrix that look like a
variance covariance matrix (correct dimensions and row and column labels), but
the values I get do not agree with what the summary() function displays -- they
also seem implausibly small.

any hints?

Thanks!

Sam

Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no
thanks Roger!

In my haste, I mistyped.  I meant to write:

sqrt(diag(mod1$fit[["imat"]]))

which should be equivalent to

summary(mod1)$Coef[,2],

the standard errors of the regression coefficients.

In any case, I have managed to replicate the case where the two commands produce
different results. Using the "columbus data"...

library(spdep)
data(columbus)

#defining W

columbus_poly <- readShapePoly(system.file("etc/shapes/columbus.shp",
package="spdep")[1])
columbus_nb <- poly2nb(columbus_poly)
columbus_listw <- nb2listw(columbus_nb)

#running spautolm()

mod1 <- spautolm(CRIME ~ HOVAL +  DISCBD,listw=columbus_listw,data =
columbus,family="SAR")

sqrt(diag(mod1$fit[["imat"]]))

summary(mod1)$Coef[,2]

and the result:
sqrt(diag(mod1$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD 
0.468345807 0.009013047 0.146973631
summary(mod1)$Coef[,2]
(Intercept)       HOVAL      DISCBD 
 4.68573639  0.09017431  1.47045128 

looks like the decimal place is shifted over one place.  If you add more
variables to the model, the results differ by more then a decimal place in this
case (in my case the results are very different). For example,

mod2 <- spautolm(CRIME ~ HOVAL +  DISCBD + INC + PLUMB,listw=columbus_listw,data
= columbus,family="SAR")

sqrt(diag(mod2$fit[["imat"]]))

summary(mod2)$Coef[,2]

results in:
sqrt(diag(mod2$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD         INC       PLUMB 
 0.52884967  0.01002545  0.17186710  0.03379109  0.04940024
summary(mod2)$Coef[,2]
(Intercept)       HOVAL      DISCBD         INC       PLUMB 
 4.86800598  0.09228322  1.58201870  0.31104348  0.45472408 

Initially, I just wanted the standard errors so that I could write them out in a
text file and put them in a table for a MSWord document.  However, I will also
need the covariances of the parameters and, thus, need the off diagonal elements
of the variance covariance matrix.   Am I reading this matrix incorrectly?

thanks for all of your help!

Sam

Quoting Roger Bivand <Roger.Bivand at nhh.no>:
On Mon, 5 Nov 2007, Sam Field wrote:

List,

I would like to grab the standard errors of the regression parameters from
an
spautolm object.  Currently I am using...

mod1 <- spautolm(y~var1 + var2,....)

mod1_sd <-  (diag(mod1$fit[["imat"]])^2
As with most model fitting functions, you use the summary method, so

summary(mod1)$Coef

is a four-column matrix, and

summary(mod1)$Coef[,2]

is the column you want.

Roger

PS. Reading summary.spautolm shows that the diagonal values of the matrix 
you refer to are the squares of the SE values.

This does produce a vector of the diagonal elements of a matrix that look
like a
variance covariance matrix (correct dimensions and row and column labels),
but
the values I get do not agree with what the summary() function displays --
they
also seem implausibly small.

any hints?

Thanks!

Sam

-- 
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no

********Note the new contact information*******

Samuel H. Field, Ph.D. 
Senior Research Investigator
CHERP/Division of Internal Medicine - University of Pennsylvania
Philadelphia VA Medical Center
3900 Woodland Ave (9 East)
Philadelphia, PA 19104
(215) 823-5800 EXT. 6155 (Office)
(215) 823-6330 (Fax)

thanks Roger!

In my haste, I mistyped.  I meant to write:

sqrt(diag(mod1$fit[["imat"]]))

which should be equivalent to

summary(mod1)$Coef[,2],

the standard errors of the regression coefficients.
No, because the fit[["imat"]] matrix has not been multiplied by s^2 (in 
summary.spautolm):

     object$resvar <- object$fit$s2 * object$fit$imat

So:
summary(mod1)$Coef[,2]
(Intercept)       HOVAL      DISCBD
  4.68573631  0.09017431  1.47045126
sqrt(diag(mod1$fit$s2 * mod1$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD
  4.68573631  0.09017431  1.47045126

And it is not multiplied in spautolm() because of the adj.se= argument to 
summary.spautolm, so that the SE values in Waller and Gotway - adjusting 
s^2 for the number of fitted coefficients - could be reproduced.

Roger

In any case, I have managed to replicate the case where the two commands produce
different results. Using the "columbus data"...

library(spdep)
data(columbus)

#defining W

columbus_poly <- readShapePoly(system.file("etc/shapes/columbus.shp",
package="spdep")[1])
columbus_nb <- poly2nb(columbus_poly)
columbus_listw <- nb2listw(columbus_nb)

#running spautolm()

mod1 <- spautolm(CRIME ~ HOVAL +  DISCBD,listw=columbus_listw,data =
columbus,family="SAR")

sqrt(diag(mod1$fit[["imat"]]))

summary(mod1)$Coef[,2]

and the result:

sqrt(diag(mod1$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD
0.468345807 0.009013047 0.146973631

summary(mod1)$Coef[,2]
(Intercept)       HOVAL      DISCBD
4.68573639  0.09017431  1.47045128

looks like the decimal place is shifted over one place.  If you add more
variables to the model, the results differ by more then a decimal place in this
case (in my case the results are very different). For example,

mod2 <- spautolm(CRIME ~ HOVAL +  DISCBD + INC + PLUMB,listw=columbus_listw,data
= columbus,family="SAR")

sqrt(diag(mod2$fit[["imat"]]))

summary(mod2)$Coef[,2]

results in:

sqrt(diag(mod2$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD         INC       PLUMB
0.52884967  0.01002545  0.17186710  0.03379109  0.04940024
summary(mod2)$Coef[,2]
(Intercept)       HOVAL      DISCBD         INC       PLUMB
4.86800598  0.09228322  1.58201870  0.31104348  0.45472408

Initially, I just wanted the standard errors so that I could write them out in a
text file and put them in a table for a MSWord document.  However, I will also
need the covariances of the parameters and, thus, need the off diagonal elements
of the variance covariance matrix.   Am I reading this matrix incorrectly?

thanks for all of your help!

Sam

Quoting Roger Bivand <Roger.Bivand at nhh.no>:

On Mon, 5 Nov 2007, Sam Field wrote:

List,

I would like to grab the standard errors of the regression parameters from
an
spautolm object.  Currently I am using...

mod1 <- spautolm(y~var1 + var2,....)

mod1_sd <-  (diag(mod1$fit[["imat"]])^2
As with most model fitting functions, you use the summary method, so

summary(mod1)$Coef

is a four-column matrix, and

summary(mod1)$Coef[,2]

is the column you want.

Roger

PS. Reading summary.spautolm shows that the diagonal values of the matrix
you refer to are the squares of the SE values.

This does produce a vector of the diagonal elements of a matrix that look
like a
variance covariance matrix (correct dimensions and row and column labels),
but
the values I get do not agree with what the summary() function displays --
they
also seem implausibly small.

any hints?

Thanks!

Sam

--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no

Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no
Maybe spautolm() rescales the coordinates before calculating the model
parameters. In that case maybe het units mod1$fit are in the new scale
and the units of summary() in the original scale.

HTH,

Thierry

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

Do not put your faith in what statistics say until you have carefully
considered what they do not say.  ~William W. Watt
A statistical analysis, properly conducted, is a delicate dissection of
uncertainties, a surgery of suppositions. ~M.J.Moroney

-----Oorspronkelijk bericht-----
Van: r-sig-geo-bounces at stat.math.ethz.ch
[mailto:r-sig-geo-bounces at stat.math.ethz.ch] Namens Sam Field
Verzonden: maandag 5 november 2007 23:19
Aan: Roger.Bivand at nhh.no
CC: r-sig-geo at stat.math.ethz.ch
Onderwerp: Re: [R-sig-Geo] spautolm - standard errors of regression
paramters

thanks Roger!

In my haste, I mistyped.  I meant to write:

sqrt(diag(mod1$fit[["imat"]]))

which should be equivalent to

summary(mod1)$Coef[,2],

the standard errors of the regression coefficients.

In any case, I have managed to replicate the case where the two commands
produce different results. Using the "columbus data"...

library(spdep)
data(columbus)

#defining W

columbus_poly <- readShapePoly(system.file("etc/shapes/columbus.shp",
package="spdep")[1])
columbus_nb <- poly2nb(columbus_poly)
columbus_listw <- nb2listw(columbus_nb)

#running spautolm()

mod1 <- spautolm(CRIME ~ HOVAL +  DISCBD,listw=columbus_listw,data =
columbus,family="SAR")

sqrt(diag(mod1$fit[["imat"]]))

summary(mod1)$Coef[,2]

and the result:
sqrt(diag(mod1$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD 
0.468345807 0.009013047 0.146973631
summary(mod1)$Coef[,2]
(Intercept)       HOVAL      DISCBD 
 4.68573639  0.09017431  1.47045128 

looks like the decimal place is shifted over one place.  If you add more
variables to the model, the results differ by more then a decimal place
in this case (in my case the results are very different). For example,

mod2 <- spautolm(CRIME ~ HOVAL +  DISCBD + INC +
PLUMB,listw=columbus_listw,data = columbus,family="SAR")

sqrt(diag(mod2$fit[["imat"]]))

summary(mod2)$Coef[,2]

results in:
sqrt(diag(mod2$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD         INC       PLUMB 
 0.52884967  0.01002545  0.17186710  0.03379109  0.04940024
summary(mod2)$Coef[,2]
(Intercept)       HOVAL      DISCBD         INC       PLUMB 
 4.86800598  0.09228322  1.58201870  0.31104348  0.45472408 

Initially, I just wanted the standard errors so that I could write them
out in a text file and put them in a table for a MSWord document.
However, I will also need the covariances of the parameters and, thus,
need the off diagonal elements
of the variance covariance matrix.   Am I reading this matrix
incorrectly?

thanks for all of your help!

Sam

Quoting Roger Bivand <Roger.Bivand at nhh.no>:
On Mon, 5 Nov 2007, Sam Field wrote:

List,

I would like to grab the standard errors of the regression 
parameters from
an
spautolm object.  Currently I am using...

mod1 <- spautolm(y~var1 + var2,....)

mod1_sd <-  (diag(mod1$fit[["imat"]])^2
As with most model fitting functions, you use the summary method, so

summary(mod1)$Coef

is a four-column matrix, and

summary(mod1)$Coef[,2]

is the column you want.

Roger

PS. Reading summary.spautolm shows that the diagonal values of the 
matrix you refer to are the squares of the SE values.

This does produce a vector of the diagonal elements of a matrix that
look
like a
variance covariance matrix (correct dimensions and row and column 
labels),
but
the values I get do not agree with what the summary() function 
displays --
they
also seem implausibly small.

any hints?

Thanks!

Sam

--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School 
of Economics and Business Administration, Helleveien 30, N-5045 
Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no

--
********Note the new contact information*******

Samuel H. Field, Ph.D. 
Senior Research Investigator
CHERP/Division of Internal Medicine - University of Pennsylvania
Philadelphia VA Medical Center 3900 Woodland Ave (9 East) Philadelphia,
PA 19104
(215) 823-5800 EXT. 6155 (Office)
(215) 823-6330 (Fax)

_______________________________________________
R-sig-Geo mailing list
R-sig-Geo at stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/r-sig-geo

Maybe spautolm() rescales the coordinates before calculating the model
parameters. In that case maybe het units mod1$fit are in the new scale
and the units of summary() in the original scale.
No, no rescaling or other tricks. The code is quite clear, the returned 
matrix is not premultiplied by s^2 - see my other reply.

Roger
HTH,

Thierry

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
www.inbo.be

Do not put your faith in what statistics say until you have carefully
considered what they do not say.  ~William W. Watt
A statistical analysis, properly conducted, is a delicate dissection of
uncertainties, a surgery of suppositions. ~M.J.Moroney

-----Oorspronkelijk bericht-----
Van: r-sig-geo-bounces at stat.math.ethz.ch
[mailto:r-sig-geo-bounces at stat.math.ethz.ch] Namens Sam Field
Verzonden: maandag 5 november 2007 23:19
Aan: Roger.Bivand at nhh.no
CC: r-sig-geo at stat.math.ethz.ch
Onderwerp: Re: [R-sig-Geo] spautolm - standard errors of regression
paramters

thanks Roger!

In my haste, I mistyped.  I meant to write:

sqrt(diag(mod1$fit[["imat"]]))

which should be equivalent to

summary(mod1)$Coef[,2],

the standard errors of the regression coefficients.

In any case, I have managed to replicate the case where the two commands
produce different results. Using the "columbus data"...

library(spdep)
data(columbus)

#defining W

columbus_poly <- readShapePoly(system.file("etc/shapes/columbus.shp",
package="spdep")[1])
columbus_nb <- poly2nb(columbus_poly)
columbus_listw <- nb2listw(columbus_nb)

#running spautolm()

mod1 <- spautolm(CRIME ~ HOVAL +  DISCBD,listw=columbus_listw,data =
columbus,family="SAR")

sqrt(diag(mod1$fit[["imat"]]))

summary(mod1)$Coef[,2]

and the result:

sqrt(diag(mod1$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD
0.468345807 0.009013047 0.146973631

summary(mod1)$Coef[,2]
(Intercept)       HOVAL      DISCBD
4.68573639  0.09017431  1.47045128

looks like the decimal place is shifted over one place.  If you add more
variables to the model, the results differ by more then a decimal place
in this case (in my case the results are very different). For example,

mod2 <- spautolm(CRIME ~ HOVAL +  DISCBD + INC +
PLUMB,listw=columbus_listw,data = columbus,family="SAR")

sqrt(diag(mod2$fit[["imat"]]))

summary(mod2)$Coef[,2]

results in:

sqrt(diag(mod2$fit[["imat"]]))
(Intercept)       HOVAL      DISCBD         INC       PLUMB
0.52884967  0.01002545  0.17186710  0.03379109  0.04940024
summary(mod2)$Coef[,2]
(Intercept)       HOVAL      DISCBD         INC       PLUMB
4.86800598  0.09228322  1.58201870  0.31104348  0.45472408

Initially, I just wanted the standard errors so that I could write them
out in a text file and put them in a table for a MSWord document.
However, I will also need the covariances of the parameters and, thus,
need the off diagonal elements
of the variance covariance matrix.   Am I reading this matrix
incorrectly?

thanks for all of your help!

Sam

Quoting Roger Bivand <Roger.Bivand at nhh.no>:

On Mon, 5 Nov 2007, Sam Field wrote:

List,

I would like to grab the standard errors of the regression
parameters from
an
spautolm object.  Currently I am using...

mod1 <- spautolm(y~var1 + var2,....)

mod1_sd <-  (diag(mod1$fit[["imat"]])^2
As with most model fitting functions, you use the summary method, so

summary(mod1)$Coef

is a four-column matrix, and

summary(mod1)$Coef[,2]

is the column you want.

Roger

PS. Reading summary.spautolm shows that the diagonal values of the
matrix you refer to are the squares of the SE values.

This does produce a vector of the diagonal elements of a matrix that

look
like a
variance covariance matrix (correct dimensions and row and column
labels),
but
the values I get do not agree with what the summary() function
displays --
they
also seem implausibly small.

any hints?

Thanks!

Sam

--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School
of Economics and Business Administration, Helleveien 30, N-5045
Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no

--
********Note the new contact information*******

Samuel H. Field, Ph.D.
Senior Research Investigator
CHERP/Division of Internal Medicine - University of Pennsylvania
Philadelphia VA Medical Center 3900 Woodland Ave (9 East) Philadelphia,
PA 19104
(215) 823-5800 EXT. 6155 (Office)
(215) 823-6330 (Fax)

_______________________________________________
R-sig-Geo mailing list
R-sig-Geo at stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/r-sig-geo

Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no