similar to: max-min plot

Hola, no me funciona: Te contesto lo mismo que le contesté a otro compañero de la lista, espero ser más claro. Les comparto la carpeta con la capa y los datos que estoy usando. https://www.dropbox.com/s/umy0evt3qm1wr4d/dissolve.zip Esto es lo que estoy haciendo: library(rgdal) library(maptools) library(sp) library(classInt) library(RColorBrewer) zm <- readOGR(?.?, ?zmdis?) data <-

Hola, El problema con la propuesta de Olivier es que los intervalos son diferentes para cada variable. La forma sencilla y rápida es: spplot(zm["part88"], col.regions=plotclr, at=class$brks) Pero para que quede más elegante hay que dar algunos pasos más: ## Intervalos en forma character op <- options(digits=4) tab <- print(class) options(op) intChar <- names(tab) ## Indice

Hola, Intento representar en un mapa participaciones porcentuales de los sectores económicos y no logro hacerlo con spplot. He intentado con spplot(zm, c(?part88?, ?part93?), cuts=4, col.regions=brewer.pal(4, ?Set3?)) Lo pude hacer utilizando el base graphics de R, definiendo: > plotvar88 <- zm$part88 > nclr <- 8 > plotclr <- brewer.pal(nclr, "PuOr") > plotclr

Dear R-helpers, I'd like to understand how to test the statistical significance of a random effect in gamm. I am using gamm because I want to test a model with an AR(1) error structure, and it is my understanding neither gam nor gamm4 will do the latter. The data set includes nine short interrupted time series (single case designs in education, sometimes called N-of-1 trials in medicine)

Hola, Estoy tratando de sobreponer un mapa sobre otro, uno que sirva de ?background? y otro con datos. Mi primer intento lo hice usando el paquete PBSmapping. Aquí lo que hice: library(PBSmapping) estados <- importShapefile(?Entidades_2013.shp") #Aquí cargamos las entidades federativas (32 entidades) zonas <- importShapefile(?zm.shp?) #Aquí cargamos las zonas metropolitanas del país

I have the following daily exchange rate series (from january 1st 1996 to december 31st 2008) and I want to obtain them monthly series from it. I've read about the 'zoo' library but I'm not getting it how to do it. These are the data (left column day-month-year, right column the index) 31/12/1993 1,12509 03/01/1994 1,12509 04/01/1994 1,12558 05/01/1994 1,1258 06/01/1994 1,12596

I am simulating an ANOVA model and get a strange behavior from the summary function. To be more specific: please run the following code and see for yourself: the summary()[["r.squared"]] values of two identical models are quite different!! ## 3 x 3 ANOVA of two factors x and z on outcome y s.size <- 300 # the sample size p.z <- c(0.25, 0.5, 0.25) # the probabilities of factor z ##

Hi, I have a question on generating random variables based on zipf-mandelbrot distribution. So when I execute the following lines: ZM = lnre ("zm", alpha = 2/3, B=0.1) zmsample = rlnre (ZM, n =100) zmsample It generates 100 random values based on a zipf-mandelbrot distribution as below. But how do I make sure the generated random number is within the range of 1 - 6000 only? Can I

Using R, I plotted a log-log plot of the frequencies in the Brown Corpus using plot(sort(file.tfl$f, decreasing=TRUE), xlab="rank", ylab="frequency", log="x,y") However, I would also like to add lines showing the curves for a Zipfian distribution and for Zipf-Mandelbrot. I have seen these in many articles that used R in creating graphs. Thank you! [[alternative HTML

Inthe code below I was trying to to obtain the GMM estimates for CAPM (REGRESSION) for 36 stocks each have 180 observations,however it only gives me one output rather than 36. In SAS i would just put in a *By statement*. I have a variable TICKER that categorize them into 36 groups. *How can I obtain all 36 output instead of just one.* **

I am working on a simple pilot project comparing the capability of SQL, SAS and R to perform a rolling mean per the following instructions. I have completed the SQL and SAS analysis, so now it's R's turn. Calculate mean values of x (x=count) for each date in the dataset where mean = the average count of days [t-9] through day [t-3] for each date/illness combination. Dataset aggpilot

Hi everyone, I have dataset which I make a sample of it couple of times and each time I get the mean and standard deviation of each row for each sample. I have a function for that, which takes the name of the file and number of times to sample and then returns the mean and standard deviation for each row in each sample. Sample=function(name, n){

Hi all R users, I want to create a matrix having n columns and 2^n rows, and all its entries are only 0 or 1. In each row, column i is 0 means dimension i is chosen, 0 means not. The matrix will contains all the possible combination of those n dimensions. Here is an example, if n = 3, the matrix will look like: 0 0 0 0 0 1 0 1 0 1 0 0 0 1 1 1 0 1 1 1 1 I know I can use n "for" loops

I''m having this issue where "puppetd -v -o" hangs (won''t return my prompt) when starting a daemon I wrote. If puppetd is running as a daemon a zombie process is created each time puppetd tries to start my daemon. Puppet detects when the daemon is down and starts it just fine. I''m using version 0.22.3 on RHEL 5. Here''s the class. I''ve

Hi, today i wrote a function in R of the type: index.refraction <- function(Temp,Press, RH, CO2) When i try to plug a negative number in Temp, i got this type of error: " n <- index.refraction(Temp= -40,100,80,CO2) Messages d'avis : 1: In Ops.ordered(left, right) : '-' is not meaningful for ordered factors 2: In Ops.factor(left, right) : - not meaningful for factors 3:

Dear all, I have a dataset. I want to make barplot from this data. Zero1 <- " V1 V2 V3 V4 V5 V6 V7 V8 V9 1 1 0 0 0 1 0 0 0 Positive 2 0 0 1 0 1 0 1 1 Negative 3 0 0 1 0 0 0 1 1 Positive 4 0 1 0 1 1 1 0 1 Negative 5 0 0 1 0 1 1 0 0 Positive 6 0 1 0 0 1 1 1 1 Negative 7 1 0 1 1 1 1 1 1 Negative 8 0 0 0 0 1 0 0 1

Hi Everyone, is there the possibility in R to assign a variable to be an alias of another one? Example: x <- 17 # assign y to be an alias of x y # returns 17 x <- 4 y # returns 4 Daniel

I am using arima to develop a time series regression model, I am using arima b/c I have autocorrelated errors. Several of my independent variables are categorical and I have coded them as factors . When I run ARIMA I don't get any warning or error message, but I do not seem to get estimates for all the levels of the factor. Can/how does ARIMA handle factors in xreg? here is some example

---------- Forwarded message ---------- From: Freddy Gamma <freddy.gamma@gmail.com> Date: 2011/1/21 Subject: TRADUCING lmer() syntax into lme() To: r-sig-mixed-models@r-project.org Dear Rsociety, I'd like to kingly ask to anyone is willing to answer me how to implement a NON NESTED random effects structure in lme() In particular I've tried the following translation from lmer to

Hello all. Why doesn't this work? d=data.frame(y=rpois(10,1),x=rnorm(10),z=rnorm(10),grp=rep(c('a','b'),each=5)) library(lme4) model=lmer(y~x+z+(1|grp),family=poisson,data=d) update(model,~.-z)###works, removes z var='z' update(model,~.-get(var))##doesn't remove z update(model,~. -get(var,pos=d))###doesn't remove z I am trying to remove z from the model in