8 Apr
2010
8 Apr
'10
2:37 p.m.
That's great. I'm glad that you figured it out.
Kosuke
--
Department of Politics
Princeton University
http://imai.princeton.edu
On Thu, 8 Apr 2010, Cesar Zucco wrote:
Just realized that converting the clustering variable
pty to a numeric
vector (instead of a factor) solves the problem!
Sorry for the trouble!
Cesar
-----Original Message-----
From: Cesar Zucco [mailto:zucco@princeton.edu]
Sent: Wednesday, April 07, 2010 8:46 PM
To: Kosuke Imai; sayan dasgupta
Cc: zelig(a)lists.gking.harvard.edu; Terry Therneau; Terry Therneau
Subject: Re: [zelig] Re: robust se's in zelig's tobit
Dear Sayan,
Here's a quick follow up to the cluster issue in Zelig that circulated a
few
days back. Sorry to keep you on this.
I was able to run clustering with tobit in Zelig but I'm having some
trouble
with the post-estimation commands. If I ran this without clustering,
post
estimation works fine:
tob4 <-
zelig(mrelideal~relideo+incab+prespty+legis,model="tobit",data=data.set)
x.out <- setx(tob4,incab=0,legis=1995,relideo=mean(data.set$relideo))
x.in <- setx(tob4,incab=1,legis=1995,relideo=mean(data.set$relideo))
x.out
(Intercept) relideo incab presptyTRUE legis1990 legis1995 legis2000
1 1 2.086757 0 0 0 1 0
sims <- sim(tob4, x = x.out, x1 = x.in)
However, if I ran this with the clustering, setx does not treat the
clustering correctly.
tob4 <-
zelig(mrelideal~relideo+incab+prespty+legis,cluster="pty",robust=T,
model="tobit",data=data.set)
x.out <- setx(tob4,incab=0,legis=1995,relideo=mean(data.set$relideo))
x.in <- setx(tob4,incab=1,legis=1995,relideo=mean(data.set$relideo))
x.out
(Intercept) relideo incab presptyTRUE legis1990 legis1995 legis2000
cluster(pty)PC cluster(pty)PN cluster(pty)NE
1 1 2.086757 0 0 0 1 0
0 0 0
sim(tob4, x = x.out, x1 = x.in)
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Error in sim.coef %*% t(x) : non-conformable
arguments
I tried getting rid of the extra values in x.out by brute force (by
deleting
any columns with cluster in the name but I think sim is using the wrong
variance-cov matrix to draw the simulations.
Any workarounds?
Thanks,
Cesar Zucco
On 3/19/10 8:54 AM, "Kosuke Imai" <kimai(a)Princeton.Edu> wrote:
Great. Thanks, Sayan!
Kosuke
9 Apr
9 Apr
3:28 p.m.
New subject: Missing values in x
Dear Colleagues,
I am running an "ls" model in Zelig, using the following code:
z.out <-
zelig(primpac~lg_nrpar+I(lg_nrpar^2)+complem+ac+r_object+r_tracost+q_2+q_6+b
efore+senior+pr_eufp+thematic+instrument+lg_pr_duration+lg_pr_funding+q_16+q
_20+q_23a+q_23b+q_23c+q_23d+q_23e+q_23f+commun+coord+dynam+uni_vs_entr,
model = "ls",
robust = TRUE,data = Dataset)
Then I set the range of values of my variable of interest:
size.range <- seq(from = 0.301, to = 2.076, by = 0.10)
And then I set x.low and x.high as follows:
x.low <- setx(z.out, pr_eufp = 0, lg_nrpar = size.range)
x.high <- setx(z.out, pr_eufp = 1, lg_nrpar = size.range)
When I run
s.out <- sim(z.out, x = x.low, x1 = x.high)
I get the following error message:
ERROR: infinite or missing values in 'x'
Can please anyone explain the meaning of this message and what am I doing
wrong?
Many thanks in advance,
Yiannis
*************************************************
Dr Yiannis Spanos, Assistant Professor of Strategy Athens University
of Economics and Business (AUEB) Department of Management Science and
Technology 47A Evelpidon Street & 33 Lefkados Street,
113 62 Athens, Greece
Tel: + 210 8203 668, Fax: + 210 8828 078
************************
"To salvage a general principle from a mass of conflicting evidence
can be both science and poetry."
L. Durrell, Monsieur - The Avignon Quintet
******************************************************
10 Apr
10 Apr
9:35 a.m.
New subject: Missing values in x
zelig does not handle missing values. You might want to try
multiply-impute the missing data using the software such as Amelia and
then use them in zelig.
Kosuke
--
Department of Politics
Princeton University
http://imai.princeton.edu
On Fri, 9 Apr 2010, Yiannis E. Spanos wrote:
Dear Colleagues,
I am running an "ls" model in Zelig, using the following code:
z.out <-
zelig(primpac~lg_nrpar+I(lg_nrpar^2)+complem+ac+r_object+r_tracost+q_2+q_6+b
efore+senior+pr_eufp+thematic+instrument+lg_pr_duration+lg_pr_funding+q_16+q
_20+q_23a+q_23b+q_23c+q_23d+q_23e+q_23f+commun+coord+dynam+uni_vs_entr,
model = "ls",
robust = TRUE,data = Dataset)
Then I set the range of values of my variable of interest:
size.range <- seq(from = 0.301, to = 2.076, by = 0.10)
And then I set x.low and x.high as follows:
x.low <- setx(z.out, pr_eufp = 0, lg_nrpar = size.range)
x.high <- setx(z.out, pr_eufp = 1, lg_nrpar = size.range)
When I run
s.out <- sim(z.out, x = x.low, x1 = x.high)
I get the following error message:
ERROR: infinite or missing values in 'x'
Can please anyone explain the meaning of this message and what am I doing
wrong?
Many thanks in advance,
Yiannis
*************************************************
Dr Yiannis Spanos, Assistant Professor of Strategy Athens University
of Economics and Business (AUEB) Department of Management Science and
Technology 47A Evelpidon Street & 33 Lefkados Street,
113 62 Athens, Greece
Tel: + 210 8203 668, Fax: + 210 8828 078
************************
"To salvage a general principle from a mass of conflicting evidence
can be both science and poetry."
L. Durrell, Monsieur - The Avignon Quintet
******************************************************
-
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11 Apr
11 Apr
11:27 a.m.
New subject: viewing data with predicted values and applying data to very large holdout sets for viewing
Hi there,
Can someone please point me to the section in the zelig manual where it
tells me how to apply a model (such as the logit or weibull) and save a
dataset into my c-drive with 2 new variables appended from the model at the
end, one which has the prediction from the model appended and another
variable that has the probability associated with the category it is
predicted into.
For example (logit model)
z.out <- zelig(vote ~gender, model =
"logit", + data = turnout[1:20000,])
The saved file would enable me to compute by hand (observed + expected) and
examine the probability of predicted values etc .....
I would like to open or view this model in a package like excel as a .csv
file.
ID, gender, vote (bush or obama ), probability of voting obama
1, 33, male, obama, .73
2, 27, male, obama, .64
I also want to apply the following function, and to see how the model
performs on a large scale set of holdout data.
z.out <- zelig(vote ~ race + educate, model =
"logit", + data =
turnout[1:20000,])
x.out <- setx(z.out, data = turnout[2100:400000,])
how do I save and store this x.out (400,000) + cases for viewing in a
package like spss or excel
Finally, how do I save the 's.out' (1000 simulations) files for examination
later also
Thanks Paul
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11:37 a.m.
New subject: viewing data with predicted values and applying data to very large holdout sets for viewing
I suggest that you start by reading Chapters 3-4 of the Zelig manual.
There really is no reason to export any data from R to Excel or SPSS,
particularly because it sounds like the calculations that you want to
perform can be done with built-in Zelig commands, or at most 1 line of
R code.
On Sun, Apr 11, 2010 at 11:27 AM, paulandpenny
<paulandpen(a)optusnet.com.au> wrote:
Hi there,
Can someone please point me to the section in the zelig manual where it
tells me how to apply a model (such as the logit or weibull) and save a
dataset into my c-drive with 2 new variables appended from the model at the
end, one which has the prediction from the model appended and another
variable that has the probability associated with the category it is
predicted into.
For example (logit model)
-
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z.out <- zelig(vote ~gender, model =
"logit", + data = turnout[1:20000,])
The saved file would enable me to compute by hand (observed + expected) and
examine the probability of predicted values etc .....
I would like to open or view this model in a package like excel as a .csv
file.
ID, gender, vote (bush or obama ), probability of voting obama
1, 33, male, obama, .73
2, 27, male, obama, .64
I also want to apply the following function, and to see how the model
performs on a large scale set of holdout data.
z.out <- zelig(vote ~ race + educate, model = "logit", + data =
turnout[1:20000,])
x.out <- setx(z.out, data = turnout[2100:400000,])
how do I save and store this x.out (400,000) + cases for viewing in a
package like spss or excel
Finally, how do I save the 's.out' (1000 simulations) files for examination
later also
Thanks Paul
-
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5152
days inactive
5155
days old
4 comments
4 participants
participants (4)
-
Kosuke Imai -
Olivia Lau -
paulandpenny -
Yiannis E. Spanos