similar to: How to plot two variables using a secondary Y axis

is there a way to use the actual index value for plotting zoo objects this is the way that the index is set up and a sample range of what I would like to plot 01/01/06 00:00:00 - 01/01/06 23:45:00 { library(zoo) # chron library(chron) fmt.chron <- function(x) { chron(sub(" .*", "", x), gsub(".* (.*)", "\\1:00", x)) }} x <- structure(c(15.57, 15.5,

Hello, I have the following data.frame structure(list(Study = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,

Dear Community, I have been using two types of survival programs to analyse a data set. The first one is an R function called aftreg. The second one an STATA function called streg. Both of them include the same analyisis with a weibull distribution. Yet, results are very different. Shouldn't the results be the same? Kind regards, J -- View this message in context:

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

Hello, I have to add "Age (bar(x)=14.3) as a title on a chart. I am unable to get this to working. I have tried bquote, substitute and expression, but they are only doing a part of the job. new<- c(14.3, 18.5, 18.1, 17.7, 18, 15.9, 19.6, 17.3, 17.8, 17.5, 15.4, 16.3, 15, 17.1, 17.1, 16.4, 15.2, 16.7, 16.7, 16.9, 14.5, 16.6, 15.8, 15.2, 16.2, 15.6, 15, 17.1, 16.7, 15.6, 15, 15.8, 16.8,

We are two french students and we have a problem concerning an exercize. We don't know how to resolve it. It would be fantastic if someone can help us. Thanks. Description: This study examined how the metabolic cost of locomotion varied with speed, stride frequency and body mass. Cost was determined by measuring oxygen consumption (?vo2?), analyzing the oxygen content in air inhaled and

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

I would like to be able to shade between two lines using ggplot2 (with faceting too). But, despite reading all the documentation on the website, cant figure out how to do it (either because i am a novice or idiot - or, of course, possibly both) My data looks is readership of paid & free newspapers in london by age since 1994. The structure is reading.melt <- structure(list(Date =

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

hi I plot a series of observation data every minutes in a day as the attachment below plot(wnd,type='l',lty=1,col='red',lwd=1,xlab=xxlab,ylab=yylab,ylim=YY) In the figure, the x-axis tickment is the number of data How can I change it fore example 1h 2h 3h 4h and so on ? -- TANG Jie Email: totangjie at gmail.com Tel: 0086-2154896104 Shanghai Typhoon Institute,China

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,

Hi all, I have this figure: http://docs.google.com/Doc?id=df5zfsj4_103rjt2v4d5 created with the following steps: > x [1] 90.4 57.8 77.0 103.7 55.4 217.5 68.1 85.3 152.0 113.0 97.1 89.9 [13] 68.1 83.7 77.4 34.5 104.9 170.3 88.6 88.1 108.8 77.4 85.6 82.7 [25] 81.3 108.0 49.5 71.0 85.7 99.3 203.5 275.9 51.1 84.8 16.5 72.6 [37] 160.5 158.3 136.7 140.0 98.4 116.1

Hi, Suppose I have the following vector (data points): > x [1] 36.0 57.3 73.3 92.0 300.4 80.9 19.8 31.4 85.8 44.9 24.6 48.0 [13] 28.0 38.3 85.2 103.6 154.4 128.5 38.3 72.4 122.7 123.1 41.8 21.7 [25] 143.6 120.2 46.6 29.2 44.8 25.0 57.3 96.4 29.4 62.9 66.4 30.0 [37] 24.1 14.8 56.6 102.4 117.5 90.4 37.2 79.6 27.8 17.1 26.6 16.3 [49] 41.4 48.9 24.1

Hello, I am loading a DBF file into R via JGR and am having trouble creating small multiple histograms on a date variable. Hist() handles the variable correctly. But I've been unable to work with lattice or ggplot2 despite trying format() and as.POSIXct(). Dates are in the format "2010-05-15" and the grouping variable is categorical. I'd appreciate it if someone would provide an

Dear R list members, I'm encountering a problem with expand.model.frame(): Suppose that I define the following simple function (meant just to illustrate the problem): > fun <- function(model){ + expand.model.frame(model, all.vars(formula(model))) + } > and I have the following model, created with an explicit data argument: > mod Call:

Hi all, I have investigated the compile-time overhead of "Polly Scop Detection" pass based on LNT testing results. This mail is to share some results I have found. (1) Analysis of "SCOP Detection Pass" for PolyBench (Attached file PolyBench_SCoPs.log) Experimental results show that the "SCOP Detection pass" does not lead to significant extra compile-time

Dear all- I have a dataset (see a sample below - but the whole dataset is June 2005 - June 2008). The "LST" format is "YYMMDDHHmm" and I would like to get the hourly average of the "mph" for the summer months (spanning all years). I have been trying to use "aggregate" but am not having much success at all! any thoughts would be greatly appreciated.

Hello, Using the following lines of code, I created the following graph:

Hello, Using the following lines of code, I created the following graph:

Hi R Users, I am going to run a multiple linear regression with around 57 independent variables. Each time I run the model with just 11 variables, the results are reasonable. With increasing the number of independent variables more than 11, the coefficients will get ?NA? in the output. Is there any limitation for the number of independent variables in multiple linear regressions in R? I attached