similar to: From daily series to monthly and viceversa

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

Hi, I am new to using R for Time series analysis. I was wondering if there are any functions that can convert ARMA or ARIMA time series into their corresponding AR or MA time series representations (by calculating the corresponding AR or MA coefficients). Thanks a lot Kris.

On 10/09/2017 03:57 PM, Daniel Berlin wrote: > FWIW: Bootstrap is probably not a good test of this, there are bugs > filed where we end up with tons of loads and stores to test against > each other. That's actually fairly rare in bootstrap, as you can see. > Let me get you some test cases. > > My guess is that we should go with mustmod. I agree. -Hal > > >

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

Hello R-list members, I’m trying to make a min-avg-max plot (like a boxplot, without box and outliers, i.e., for each class of "x" a vertical line indicating the range (max-min) and an horizontal line or point indicating the mean) with data like: Year Avg Min Max 98 10 7 13 99 12 10 15 01 11 6 14 Which command should be used? Many thanks, Antonio Olinto

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, This came up in https://reviews.llvm.org/D38569, and I'd like some input on what's the best way to get alias and mod-ref info without having two alias calls. A couple of ideas: (a) Extend the getModRefInfo interface (+getModRefBehavior, +gerArgModRefInfo) to return a pair {ModRefInfo, AliasResult}. The AliasResult can be optional based on an argument e.g.: struct MRI_AR {

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

On Mon, Oct 9, 2017 at 1:57 PM, Daniel Berlin <dberlin at dberlin.org> wrote: > FWIW: Bootstrap is probably not a good test of this, there are bugs filed > where we end up with tons of loads and stores to test against each other. > That's actually fairly rare in bootstrap, as you can see. > Let me get you some test cases. > SG, thanks! > > My guess is that we

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.* **

> > Sigh > I should have taken the time to give a better example. > The must-alias part is irrelevant to an example (it only requires > read-onlyness) > > You said "LICM doesn't move calls, so we'd never really care about > must-alias for promotion". I was just pointing out other things move calls > any may want to know. > > If you want an example

I'm trying to understand what is the result we'd seek in the example in D38569 (pasting here for quick access) double f(double a) { double b; double c,d; double (*fp) (double) __attribute__ ((const)); /* Partially redundant call */ if (a < 2.0) { fp = sin; c = fp (a); } else { c = 1.0; fp = cos; } d = fp (a);

Yes, this is odd. On my clang.bc Without: 2.2967 ( 53.8%) 0.0242 ( 26.4%) 2.3210 ( 53.2%) 2.3227 ( 53.2%) Memory SSA 2.3364 ( 53.7%) 0.0246 ( 25.7%) 2.3610 ( 53.1%) 2.3636 ( 53.1%) Memory SSA 2.3353 ( 54.0%) 0.0258 ( 27.0%) 2.3611 ( 53.4%) 2.3632 ( 53.3%) Memory SSA With two getModRefInfo calls: 3.0302 ( 58.8%) 0.0328 ( 29.9%) 3.0630 ( 58.2%) 3.0858 ( 58.2%)

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 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

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