Zelig April 2006

zelig@lists.gking.harvard.edu

5 participants
6 discussions

by Humphrey, Timothy L. (LNG-DAY)

By the way, I got the same error when I used the data and zelig command in Example 1 on page 253 of the Zelig manual, i.e. this is section 12.26 on relogit. Here is the code for that attempt. > data(mid) > z.out1 <- zelig(conflict ~ major + contig + power + maxdem + mindem + years, data=mid, model = "relogit", tau=1042/303772) > x.out1 <- setx(z.out1,data=mid, fn=NULL,cond=T) > s.out1 <- sim(z.out1, x=x.out1) Error in yvar - qi$ev : non-conformable arrays _____ From: owner-zelig(a)mail-1.hmdc.harvard.edu [mailto:owner-zelig@mail-1.hmdc.harvard.edu] On Behalf Of Humphrey, Timothy L. (LNG-DAY) Sent: Thursday, April 20, 2006 3:29 PM To: zelig(a)latte.harvard.edu Subject: [zelig] Error when using sim. I'm attempting to use relogit. I want to make a model then have the model predict the outcome on test data. I was told that I can't use the R predict function to do the prediction. So, I have been reading the manual to learn how to do prediction. After reading the manual I produced the following code. But, when I run it, I always get an error after running the sim function (See below) > z.out <- zelig(my.formula, data=LR.data, model = "relogit", tau=0.05) > x.out <- setx(z.out, data=test.d, fn=NULL, cond=TRUE) > s.out <- sim( z.out, x = x.out ) Error in yvar - qi$ev : non-conformable arrays In the above example, x.out has 20 samples with 15 explanatory variables. In addition, when I run sim with x.out having 10,000 samples, I get a memory limits exceeded error. Below is what x.out looks like for the above example: > x.out cbind(Y, 1 - Y).Y cbind(Y, 1 - Y).V2 X1 X2 X3 X4 X5 X6 X7 X8 1 0 1 0.0000 1.0 0 0 1.0 0.0 0.0000 0.0000 2 0 1 0.0000 0.5 0 0 0.5 0.0 0.0000 0.0000 3 0 1 0.1397 0.5 0 0 0.0 0.5 0.2732 1.0000 4 0 1 0.1397 0.0 0 0 0.0 0.0 0.0000 0.0000 5 0 1 0.0000 1.0 0 0 0.0 0.0 0.0000 0.0000 6 0 1 0.1397 0.5 0 0 0.0 0.5 0.2732 0.0000 7 0 1 0.1397 1.0 0 0 0.5 0.0 0.2732 0.0000 8 0 1 0.2708 1.0 0 0 0.0 0.0 0.0000 0.0664 9 0 1 0.1397 1.0 0 0 1.0 0.0 1.0000 0.0000 10 0 1 0.5270 0.0 0 1 0.0 0.0 0.2732 0.0000 11 1 0 0.0000 0.0 0 0 1.0 0.0 0.2732 0.0000 12 1 0 0.0000 1.0 0 1 1.0 0.0 0.0000 0.0000 13 1 0 0.7583 0.0 0 1 0.5 0.5 0.2732 1.0000 14 1 0 0.1328 0.0 0 0 1.0 0.0 0.0000 0.0000 15 1 0 0.5270 0.0 0 0 0.0 0.0 1.0000 0.0000 16 1 0 0.1328 0.0 0 1 0.0 0.0 0.0000 0.0000 17 1 0 0.0000 1.0 0 0 0.0 0.0 0.0000 0.0000 18 1 0 0.5270 0.5 0 0 1.0 0.0 1.0000 0.0000 19 1 0 1.0000 0.0 0 1 0.0 0.5 1.0000 0.0664 20 1 0 1.0000 0.0 0 0 0.0 0.0 1.0000 0.0000 X9 X10 X11 X12 X13 X14 X15 1 0 0.0000 0.2700 0.1506 0.2498 0.5077 0 2 0 0.0000 0.0601 0.0000 0.1683 0.5077 0 3 0 0.0000 0.0424 0.1506 0.3022 0.7333 0 4 0 0.0000 0.1316 0.3939 0.1417 0.5077 0 5 0 0.1576 0.7785 0.0000 0.2882 0.3143 0 6 0 0.0000 0.0601 0.7959 0.2845 0.5077 0 7 0 0.1576 0.4845 0.0000 0.0231 0.3143 0 8 0 0.0000 0.4061 0.1506 0.0000 0.0000 0 9 0 0.0000 0.3014 0.2063 0.0264 0.5077 1 10 0 0.0000 0.3014 0.4643 0.3881 0.1467 0 11 0 0.0000 0.2034 0.5392 0.2418 0.5077 1 12 0 0.0000 0.1388 0.0000 0.1025 0.1467 0 13 1 0.0000 0.0508 0.2063 0.3312 0.5077 0 14 0 0.0000 0.2215 0.0476 0.2499 0.5077 0 15 0 0.1576 0.6463 0.1506 0.2182 0.5077 0 16 0 0.1576 0.3346 0.4643 0.7887 0.5077 0 17 0 0.1576 0.4845 0.0000 0.0350 0.1467 0 18 0 0.0000 0.0984 0.1506 0.0714 0.1467 0 19 0 0.0000 0.1462 0.0000 0.0000 0.0000 0 20 0 0.0000 0.1777 0.3277 0.3560 0.7333 0

18 years

Error when using sim.

by Humphrey, Timothy L. (LNG-DAY)

I'm attempting to use relogit. I want to make a model then have the model predict the outcome on test data. I was told that I can't use the R predict function to do the prediction. So, I have been reading the manual to learn how to do prediction. After reading the manual I produced the following code. But, when I run it, I always get an error after running the sim function (See below) > z.out <- zelig(my.formula, data=LR.data, model = "relogit", tau=0.05) > x.out <- setx(z.out, data=test.d, fn=NULL, cond=TRUE) > s.out <- sim( z.out, x = x.out ) Error in yvar - qi$ev : non-conformable arrays In the above example, x.out has 20 samples with 15 explanatory variables. In addition, when I run sim with x.out having 10,000 samples, I get a memory limits exceeded error. Below is what x.out looks like for the above example: > x.out cbind(Y, 1 - Y).Y cbind(Y, 1 - Y).V2 X1 X2 X3 X4 X5 X6 X7 X8 1 0 1 0.0000 1.0 0 0 1.0 0.0 0.0000 0.0000 2 0 1 0.0000 0.5 0 0 0.5 0.0 0.0000 0.0000 3 0 1 0.1397 0.5 0 0 0.0 0.5 0.2732 1.0000 4 0 1 0.1397 0.0 0 0 0.0 0.0 0.0000 0.0000 5 0 1 0.0000 1.0 0 0 0.0 0.0 0.0000 0.0000 6 0 1 0.1397 0.5 0 0 0.0 0.5 0.2732 0.0000 7 0 1 0.1397 1.0 0 0 0.5 0.0 0.2732 0.0000 8 0 1 0.2708 1.0 0 0 0.0 0.0 0.0000 0.0664 9 0 1 0.1397 1.0 0 0 1.0 0.0 1.0000 0.0000 10 0 1 0.5270 0.0 0 1 0.0 0.0 0.2732 0.0000 11 1 0 0.0000 0.0 0 0 1.0 0.0 0.2732 0.0000 12 1 0 0.0000 1.0 0 1 1.0 0.0 0.0000 0.0000 13 1 0 0.7583 0.0 0 1 0.5 0.5 0.2732 1.0000 14 1 0 0.1328 0.0 0 0 1.0 0.0 0.0000 0.0000 15 1 0 0.5270 0.0 0 0 0.0 0.0 1.0000 0.0000 16 1 0 0.1328 0.0 0 1 0.0 0.0 0.0000 0.0000 17 1 0 0.0000 1.0 0 0 0.0 0.0 0.0000 0.0000 18 1 0 0.5270 0.5 0 0 1.0 0.0 1.0000 0.0000 19 1 0 1.0000 0.0 0 1 0.0 0.5 1.0000 0.0664 20 1 0 1.0000 0.0 0 0 0.0 0.0 1.0000 0.0000 X9 X10 X11 X12 X13 X14 X15 1 0 0.0000 0.2700 0.1506 0.2498 0.5077 0 2 0 0.0000 0.0601 0.0000 0.1683 0.5077 0 3 0 0.0000 0.0424 0.1506 0.3022 0.7333 0 4 0 0.0000 0.1316 0.3939 0.1417 0.5077 0 5 0 0.1576 0.7785 0.0000 0.2882 0.3143 0 6 0 0.0000 0.0601 0.7959 0.2845 0.5077 0 7 0 0.1576 0.4845 0.0000 0.0231 0.3143 0 8 0 0.0000 0.4061 0.1506 0.0000 0.0000 0 9 0 0.0000 0.3014 0.2063 0.0264 0.5077 1 10 0 0.0000 0.3014 0.4643 0.3881 0.1467 0 11 0 0.0000 0.2034 0.5392 0.2418 0.5077 1 12 0 0.0000 0.1388 0.0000 0.1025 0.1467 0 13 1 0.0000 0.0508 0.2063 0.3312 0.5077 0 14 0 0.0000 0.2215 0.0476 0.2499 0.5077 0 15 0 0.1576 0.6463 0.1506 0.2182 0.5077 0 16 0 0.1576 0.3346 0.4643 0.7887 0.5077 0 17 0 0.1576 0.4845 0.0000 0.0350 0.1467 0 18 0 0.0000 0.0984 0.1506 0.0714 0.1467 0 19 0 0.0000 0.1462 0.0000 0.0000 0.0000 0 20 0 0.0000 0.1777 0.3277 0.3560 0.7333 0

18 years

Newbie question--GAMs

by Thomas L Jones

Newbie question: Will Zelig handle a Generalized Additive Model with a time series with count data (Poisson distributed)? Tom A veteran computer professional who is a newbie to R and Zelig.

18 years

Re: [zelig] simulation with Zelig

by Olivia Lau

Dear Luca, If you just want to use lm() to run a weighted regression via zelig, all you need to do is: z.out <- zelig(formula = y ~ x1*x2 + x3 + x4 + x5, model="ls", data = my.data, weights = my.data$my.weights) x.out <- setx(z.out) Note that any arguments accepted by lm() are passed via ..., so it is not necessary to do any recoding. zelig(...) will do everything that lm(...) can do. You will probably need to recode your my.weights variable into a numeric variable, by changing factor = 0 into the number of 0's in the data for example. lm() will renormalize the weights for you, but R doesn't know what to do with a factor weight. Best, Olivia Lau ----- Original Message ----- From: Luca De Benedictis To: Olivia Lau Sent: Wednesday, April 05, 2006 8:43 AM Subject: Re: [zelig] simulation with Zelig Dear Olivia, thank you for the very quick reply. I did not use a new function, I believed that it was possible to modify the original "ls" function extending the number of arguments in the model. Since the "weight" argument is already present in the "lm" function I believed it was possible to make "ls" more similar to "lm" through: zelig2ls <- function(formula, model, data, M, ...) { mf <- match.call(expand.dots = TRUE) mf[[1]] <- as.name("ls") as.call(mf) } In fact when I run the weighted regression the summary(z.out) gives me the standard output. Finally, my.weights is indeed in my.data and x1 is a categorical variable that takes values 0,1,2,3; all other xs are categorical variables as well. Thank you very much for your help and let me know if you want to have a look at the dataset and the R script. All the best Luca Olivia Lau wrote: Dear Luca, To clarify: Did you write your own "ls" function to perform the procedure you describe below? If so, you might want to name the function something else as there is already a Zelig model called "ls". (I suggest "wls" since your model does something special with the weights -- you will need to change your zelig2ls function to zelig2wls, etc.) Can you verify that your data works with the following default syntax? I just want to isolate the error, whether it is in your "wls" function or in our code. First, make sure that my.weights is a variable in my.data: my.data$my.weights If not, insert into the data.frame: my.data$my.weights <- my.weights Now try: z.out <- zelig(formula = y ~ x1*x2 + x3 + x4 + x5, model="ls", data = my.data, weights = my.data$my.weights) x.out <- setx(z.out) If that works (it should, I just tested it), then the error is likely in your wls() function. Are you using our model.end() function prior to exiting wls()? setx() needs some information from your data in order to run properly and model.end() codes this. If you are using model.end(), then perhaps there is another problem and I would be happy to take a look at your code for wls(), if you send it along. Best, Olivia Lau ----- Original Message ----- From: Luca De Benedictis To: zelig(a)latte.harvard.edu Sent: Wednesday, April 05, 2006 4:16 AM Subject: [zelig] simulation with Zelig Dear Zelig-list, I am trying to use the Zelig library to simulate the following model: z.out<-zelig(formula = y ~ x1*x2 + x3 + x4 + x5, model="ls", data = my.data, weights = my.weights) Since the regression is weighted before running the regression I used the procedure: zelig2ls <- function(formula, model, data, M, ...) { mf <- match.call(expand.dots = TRUE) mf[[1]] <- as.name("ls") as.call(mf) } but when I set x.out<-setx(z.out) I receive the following error message: Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : variable lengths differ In addition: Warning message: There is more than one mode. The first level is selected. in: FUN(X[[1]], ...) Any suggestion is appreciated Luca De Benedictis http://www.economiamc.org/debenedictis

18 years, 1 month

simulation with Zelig

by Luca De Benedictis

Dear Zelig-list, I am trying to use the Zelig library to simulate the following model: z.out<-zelig(formula = y ~ x1*x2 + x3 + x4 + x5, model="ls", data = my.data, weights = my.weights) Since the regression is weighted before running the regression I used the procedure: zelig2ls <- function(formula, model, data, M, ...) { mf <- match.call(expand.dots = TRUE) mf[[1]] <- as.name("ls") as.call(mf) } but when I set x.out<-setx(z.out) I receive the following error message: Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : variable lengths differ In addition: Warning message: There is more than one mode. The first level is selected. in: FUN(X[[1]], ...) Any suggestion is appreciated Luca De Benedictis http://www.economiamc.org/debenedictis

18 years, 1 month

Re: Questions about Case Control and Rare Events.

by Gary King

thanks for your note. yes, relogit in Zelig will do everything you're interested in and so you don't need to calculate C or the var-cov matrix yourself; all the corrections are made for you. the key is to recognize that there are 2 separate forms of bias correction, one for case-control studies, for which you'd use the case.correct option, and the other for rare events bias (which is appropriate whether or not you use case control designs), for which you'd use the bias.correct option. Best of luck with your research, Gary --- Gary King, Institute for Quantitative Social Science Harvard University, 1737 Cambridge St, Cambridge, MA 02138 http://GKing.Harvard.Edu, King(a)Harvard.Edu Direct 617-495-2027, Assistant 495-9271, eFax 812-8581 On Tue, 10 Jan 2006, Dave Armstrong wrote: > Dear Prof King, > > I read your paper "Logistic Regression in Rare Events Data" and have just a > couple of quick questions about it. For consistency of notation, I've put > them in the attached PDF. If you would have some time to look at them or > point them and me in the right direction, it would be very much appreciated. > > > Thanks for your help, > > Dave. > > -- > Dave Armstrong > University of Maryland > Dept of Government and Politics > 3140 Tydings Hall > College Park, MD 20742 > Office: 2103L Cole Field House > Phone: 301-405-9735 > e-mail: darmstrong(a)gvpt.umd.edu > web: www.davearmstrong-ps.com > > Facts are meaningless. You can use facts to prove anything that's even > remotely true. - Homer Simpson > > To this day, philosophers suffer from Plato's disease: the assumption that > reality fundamentally consists of > abstract essences best described by words or geometry. (In truth, reality is > largely a probabilistic affair best > described by statistics) - Steve Sailer "The Unexpected Uselessness of > Philosophy" > - Zelig Mailing List, served by Harvard-MIT Data Center Send messages: zelig(a)latte.harvard.edu [un]subscribe Options: http://lists.hmdc.harvard.edu/?info=zelig Zelig program information: http://gking.harvard.edu/zelig/

18 years, 1 month

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

Zelig April 2006