similar to: xyplot: superpose 2 time series with different time intervals

I could use some advice. I've got 2 time series. Both cover approximately the same period of time (ie, 1940 to 2009). But one series has annual data and the other has monthly data. One refers to university enrollment; the other to unemployment rates. Both are currently in the same data frame. I'd like to use the monthly times series as a light grayscale background for a plot of the

I have a simple bar chart with annual precipitation (jan to dez). I want to plot, above each bar (on a line), a square wich is color based on a scale (0-100%). With 0 being white and 100 black, like a gradient. Is it possible? How to? Thanks -- Fernando Andreacci [[alternative HTML version deleted]]

Dear R users, I try to use xyplot() to display two different response variables from the same dataframe per panel, but don't succeed: xyplot(ptot.seaslog ~ vmcwit | seas, data=reeks, as.table=TRUE, panel = function(x,y){ panel.xyplot(x, y, ylim=c(0,1)) panel.superpose(x=reeks$vmcwit, y=reeks$ptotbin, panel.groups = "panel.xyplot",

I woud like to plot cumulative histograms. Specifically, I have data like Sex M M F M F F M F Height 6 6.3 6.1 5.5 7.2 6.2 5.9 6.0 .... and I want to plot a histogram of the distribution of all heights, colouring the histogram bars according to sex, for example | o | oo o | o oo ** o o = observations of women | o o*o***o * = observations of

I have a monthly price index series x, the related return series y = diff(log(x)) and a POSIXlt date-time variable dp. I would like to apply annual blocks to compute for example annual block maxima and mean of y. When studying the POSIX classes, in the first stage of the learning curve, I computed the maximum drawdown of x: > mdd <- maxdrawdown(x) > max.dd <- mdd$maxdrawdown > from

Folks, This question is somewhat related to a previous posting of mine. I just can't seem to create a generic solution. Here is a function that I found searching around the internet: splitIt <- function(x, n) {split(x, sort(rank(x) %% n))} I use it like so: > splitIt(1:12, 2) $`0` [1] 1 2 3 4 5 6 $`1` [1] 7 8 9 10 11 12 Or > splitIt(1:12, 4) $`0` [1] 1 2 3 $`1` [1] 4 5 6

Hi, I'd like to make a time series at an annual frequency. > a<-xts(x=c(2,4,5), order.by=c("1991","1992","1993")) Error in xts(x = c(2, 4, 5), order.by = c("1991", "1992", "1993")) : order.by requires an appropriate time-based object > a<-xts(x=c(2,4,5), order.by=1991:1993) Error in xts(x = c(2, 4, 5), order.by =

[re-sending - previous email went out by accident before complete] Hi Joe, The centering and re-scaling is done for the purposes of his example, and also to be consistent with his definition of the sharpe function. In particular, note that the sharpe function has the rf (riskfree) parameter with a default value of .03/252 i.e. an ANNUAL 3% rate converted to a DAILY rate, expressed in decimal. That

I want to load many files in the R. The names of the files are "Sim1.txt", " Sim2.txt", "Sim3.txt", "Sim4.txt", "Sim5.txt" and so on. Can I read them at one time? What should I do? I can give the same names in R. Thanks. For example: > tst=paste("Sim",1:20,".txt",sep="") # the file names > tst [1]

I am using windows XP with R 2.8.1 I am generating a lattice plot of annual rain patterns using the following function: > xyplot(rain.stats$min+ rain.stats$max + rain.stats$ave ~ rain.stats$month |rain.stats$year, lty = 1, data = rain.stats, type = c("l","l", "l"), col = c("red", "blue", "green"), distribute.type =

Hello R users It's some time I am playing with a dataset to do some cluster analysis. The data set consists of 14 columns being geographical coordinates and monthly temperatures in annual files latitutde - longitude - temperature 1 -..... - temperature 12 I have some missing values in some cases, maybe there are 8 monthly valid values at some points with four non valid. I don't want to

Dear all, My double for loop as follows, but it is little efficient, I hope all friends can give me a "vectorized" program to replace my code. thanks x: is a matrix 202*263, that is 202 samples, and 263 independent variables num.compd<-nrow(x); # number of compounds diss.all<-0 for( i in 1:num.compd) for (j in 1:num.compd) if (i!=j) { S1<-sum(x[i,]*x[j,])

Hi Eric, Thank you, that helps a lot. If I'm understanding correctly, if I?m wanting to use actual returns from backtests rather than simulated returns, I would need to make sure my risk-adjusted return measure, sharpe ratio in this case, matches up in scale with my returns (i.e. daily returns with daily sharpe, monthly with monthly, etc). And I wouldn?t need to transform returns like the

Greetings, I am attempting to build a R package, however the build fails and the following message is ouput: C:\ConstellaGroup\EPA\RAGG\package>R CMD BUILD --binary --force RAGG * checking for file 'RAGG/DESCRIPTION' ... OK * preparing 'RAGG': * checking DESCRIPTION meta-information ... ERROR Error in if (regexpr(dep_regexp, dep) == -1) { : missing value where

Dear r-help, I need to draw some lattice plots and have stuck in strange problems. I have a data frame of 405 rows: > str(dframe) `data.frame': 405 obs. of 4 variables: $ year : num 1990 1990 1990 1990 1990 1990 1990 1990 1990 1990 ... $ month: num 1 2 3 4 5 6 7 8 9 10 ... $ V_A2 : num NA NA NA NA NA ... $ V_A3 : num NA NA NA NA NA ... Variable month changes from 1 to 27

Correct Sent from my iPhone > On 21 Nov 2017, at 22:42, Joe O <joerodonnell at gmail.com> wrote: > > Hi Eric, > > Thank you, that helps a lot. If I'm understanding correctly, if I?m wanting to use actual returns from backtests rather than simulated returns, I would need to make sure my risk-adjusted return measure, sharpe ratio in this case, matches up in scale with

Dear R-users, I'm using lattice package and function xyplot for the first time so you will excuse me for my inexperience. I'm facing quite a simple problem but I'm having troubles on how to solve it, I've read tons of old mails in the archives and looked at some slides from?Deepayan Sarkar but still can not get the point. This is the context. I've got data on 9 microRNAs, each

I am trying to display data ion top of colored rectangle on the same levelplot. While using superpose the shape and symbol for levelplot changes to small circle. I am unable to figure what exactly I am doing wrong... It may be straightforward solution... .I will appreciate help to fix this issue.

Apologies for the empty email earlier! I have species abundance data sampled at a weekly frequency or sometimes monthly depending on the year. The goal is to identify the dates in an annual cycle in which the cumulative abundance of a species reaches some threshold. Here's an example of the data for 1 species over an annual period: "mc_pheno" is the object created from this data:

Hello, I'm trying currently using barplot to summarize precipitation data. So far I've compiled total annual snow and rain accumulation in a table (attached). I've been successful at plotting it using the following code: fig=barplot(t(Annual_Precip_table), horiz=TRUE, space=0, col=c("grey70", "white"), axes=FALSE) . . The result is a stacked barplot with total