Re: [R-sig-eco] How to remove space among columns
l=data.frame(col1=c(0,1,0), col2=c(1,0,1), col3=c(1, 0, 1), col4=c(0, 0,
1), col5=c("a", "a", "b"), col6=c("c", "d", "d"))
ll=paste(l$col1, l$col2, l$col3, l$col4, sep="")
data.frame(ll, a=l$col5, b=l$col6)
see ?paste
bret
On 3/27/2013 8:15 AM, Manuel Spínola wrote:
Thank you very much to all that answered my question, some one of you asked
me to be more specific, here is my question again:
I hava a data frame:
col1 col2 col3 col4 col5 col6
01 1 0 ac
10 0 0 ad
01 1 1 bd
I want to end with a data frame like this (the first 4 columns without
space):
0110 ac
1000 ad
0111 bd
Best,
Manuel
2013/3/26 Roman Luštrik
How do you want to remove the space, so that when you print a data frame
that the columns are closer together? Pr perhaps you're trying to merge
column names into a single string? Perhaps something third? Can you expand
your answer?
Cheers,
Roman
2013/3/27 Manuel SpÃnola
Dera list members,
How to remove spaces among columns in a data frame.
1 2 3 4 to become 1234
Best,
Manuel
--
*Manuel SpÃnola, Ph.D.*
Instituto Internacional en Conservación y Manejo de Vida Silvestre
Universidad Nacional
Apartado 1350-3000
Heredia
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Re: [R-sig-eco] Recode several variables with conditions in a data frame
Not very elegant or efficient, but for only a couple of columns needing left out something simple like this should work. xx=data.frame(x=c(2, 10), y=c(2, 0), z=c(4, 3)) yy=xx[,2:3] yy[yy!=0]=1 data.frame(x=xx[,1], yy) bret On 7/3/2012 9:18 PM, Manuel Spínola wrote: Thank you Bret. What if I need to leave out some variables from my data frame. I have 22 variables and I need to leave the 2 first variables out of the condition. Best, Manuel 2012/7/3 Bret Collier Manuel, Something like this should work for your example. xx=data.frame(x=c(2, 10), y=c(2, 0)) xx[xx!=0]=1 xx x y 1 1 1 2 1 0 Bret On 7/3/2012 8:12 PM, Manuel Spínola wrote: Dear list members, I want to recode a data frame but do it for several variables at the same time. I want to give all the values > or equal than 1 a value of 1 and all the remaining values (0) keep in 0. data.frame: newdf var1 var2 var3 var4 A 1 0 4 B 3 2 1 C 0 5 1 My real data frame has several more variables. I am using the recode function from the epicalc package: recode(vars=newdf[, 2:4], old.value= newdf[, 2:4] >= 1, new.value=1) Error en recode.default(vars = newdf[, 2:4], old.value = newdf[, 2:4] >= : objeto '.data' no encontrado I guess I am not setting the condition in a proper way. Best, Manuel __**_ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/**listinfo/r-sig-ecology<https://stat.ethz.ch/mailman/listinfo/r-sig-ecology> __**_ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/**listinfo/r-sig-ecology<https://stat.ethz.ch/mailman/listinfo/r-sig-ecology> ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] Recode several variables with conditions in a data frame
Manuel, Something like this should work for your example. xx=data.frame(x=c(2, 10), y=c(2, 0)) xx[xx!=0]=1 xx x y 1 1 1 2 1 0 Bret On 7/3/2012 8:12 PM, Manuel Spínola wrote: Dear list members, I want to recode a data frame but do it for several variables at the same time. I want to give all the values > or equal than 1 a value of 1 and all the remaining values (0) keep in 0. data.frame: newdf var1 var2 var3 var4 A 1 0 4 B 3 2 1 C 0 5 1 My real data frame has several more variables. I am using the recode function from the epicalc package: recode(vars=newdf[, 2:4], old.value= newdf[, 2:4] >= 1, new.value=1) Error en recode.default(vars = newdf[, 2:4], old.value = newdf[, 2:4] >= : objeto '.data' no encontrado I guess I am not setting the condition in a proper way. Best, Manuel ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] Help with nonlinear population trends & binomialregression
Matt, Check out the SemiPar package maintained by Matt Wand and see the book: Semiparametric Regression. 2003, Ruppert, Wand, and Carroll. There are some nice code in the book and online for Bayesian logistic modeling using penalized splines as well. Bret On 12/17/2010 3:04 AM, Alexandre Villers wrote: Hey Matthew, You should have a look at the Zuur et al. 2009 and the chapter 6 dealing with Violation of Independance (page 143). They explain how to fit GAMMs for different locations (species in your case). You can select models through AIC (but I guess you have to be pretty cautious with this type of model in model selection process). You should also consider adding a temporal correlation structure given you have times series (this is also explained in this book). HTH Alex On 17/12/2010 10:55, Aitor Gastón wrote: Matthew, A more flexible model may be a better option than fitting two separate lines (e.g. restricted cubic splines, rcs function of the rms package or a generalized additive model, mgcv package). A restricted cubic spline with 4 knots may be enough to model the response curve that you describe. Hope that helps, Aitor -- From: "Matthew Forister" Sent: Friday, December 17, 2010 7:19 AM To: Subject: [R-sig-eco] Help with nonlinear population trends & binomialregression Hello, I'm hoping someone can point me in a new direction with this particular issue... I have count data for many species across 20-30 years. I know that many species are declining, probably in association with habitat destruction, and I have been using binomial regression to model the declines (e.g. glm(cbind(presence,visits-presence)~years,binomial). I have also used the glm.binomial.disp function for overdispersion. So far so good, but here's the issue: not all species decline in the same way... Some go down steadily over the years, while others will be holding steady and then suddenly start on a decline. There are other patterns, but those two are dominant and I would like to be able to say that different species have these different dynamics. But how do I quantify those different curves? I have played with fitting quadratic and cubic terms within the binomial regression (e.g. glm(cbind(presence,visits-presence)~years+I(years^2),binomial)), and then comparing models with AIC to think about the better fit of the model with the quadratic. That kinda makes sense for some species, but it's far from satisfying... In the case I described (a species holding steady for 2 decades and then going into a steady decrease for another 10), what it really looks like is two different lines, one flat and one precipitous. Is there a way to ask if a given relationship is better fit by two lines than one? any other hints on how to describe these kinds of dynamics? thanks! Matt -- Matthew L Forister Assistant Professor Department of Biology / MS 314 1664 N. Virginia St. University of Nevada, Reno Reno, Nevada 89557 -- E-mail: foris...@gmail.com Office phone: (775) 784 - 6770 Lab phone: (775) 784 - 7083 Fax: (775) 784 - 1302 Office: room 257 Fleischmann Agriculture Building -- Webpage: https://sites.google.com/site/greatbasinbuglab/ -- [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] Multi-state models
Krzysztof, I probably just beat Jeff to it, but you should look into RMark, it is an interface to MARK using R, I use it all the time and it works great, help is very detailed, and multi-strata models are implemented in it. http://www.phidot.org/software/mark/rmark/ Bret Krzysztof Sakrejda-Leavitt wrote: Dear colleagues, I am am starting work on a project using multi-state models based on capture-mark-recapture data to create parameter estimates for matrix population models. The software the group is currently using is MSurge, but I am interested in packages within R which would substitute for that function. I am aware of pomp and msm, but i have experience with neither. Any comments on functionality and robustness in real applications (or in testing) would be appreciated, especially coming from anyone who has also worked with MSurge/MARK. Best, Krzysztof -- Krzysztof Sakrejda-Leavitt Organismic and Evolutionary Biology University of Massachusetts, Amherst 319 Morrill Science Center South 611 N. Pleasant Street Amherst, MA 01003 work (cell): 413-325-6555 email: [EMAIL PROTECTED] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
