similar to: text processing for plots

Hi R users,I am a beginner in the use of R. I need urgent help for my thesis study. <https://stats.stackexchange.com/posts/633206/timeline> I have daily air pollution parameters PM10, PM2.5 CO, NO2, SO2, and O3. I also have daily hospital admission numbers. Taking into account the effect of weekends and holidays, I would like to used generalised additive model (GAM) to explore the

Hi - I am trying to find and describe missing data in a time series. For instance, in the library openair, there is a data frame called "mydata": library(openair) head(mydata) date ws wd nox no2 o3 pm10 so2 co pm25 1 1998-01-01 00:00:00 0.60 280 285 39 1 29 4.7225 3.3725 NA 2 1998-01-01 01:00:00 2.16 230 NA NA NA 37 NA NA NA 3 1998-01-01 02:00:00

R Friends, I'm running R2.7.1 on Windows XP. I'm trying to get some lattice functionality which I have not seen previously documented--I'd like to plot the exact same data in multiple panels but changing the grouping variable each time so that each panel highlights a different feature of the data set. The following code does exactly that with a simple and fabricated air quality data

Funciona perfecto! Gracias Carlos. Atte. Novvier Uscuchagua De: Carlos Ortega [mailto:cof en qualityexcellence.es] Enviado el: viernes, 16 de junio de 2017 13:46 Para: Novvier Marco Uscuchagua Cornelio <novvier en outlook.com.pe> CC: r-help-es en r-project.org Asunto: Re: Varios gráficos en una vista en OpenAir Hola, Prueba entonces esto, que sí que funciona... #-----------------------

I'm working with data measured in a tunnel to estimate the emission factor of heavy & light vehicles. I tried to use 'gnls' and I get the following Error: >> Error in "coef<-.corARMA"(*tmp*, value = c(174.267493382104, 173.412740072763 : >> Coefficient matrix not invertible Here is my R-code: data <- d.plabutsch.neu # calculating the starting

Hallo Everybody How do you specify arguments for a function used within another function? Here is my problem: I am reconstructing a calculator for the burden of disease due to air pollution from publications and tools published by the WHO. The calculations make use of published dose-response relationships for particular health end-points. This is then applied to populations with known or

Dear list I'm plotting ( boxplot() and plot() ) some data for a publication. The editor would like the text labels on the plots in a larger font. I'm doing something like this: <snip> jpeg( filename = "D:/Martin/Work/CleanPath/RAF1%03d.jpg", width = 1000, height = 600, pointsize = 12, quality = 100, bg = "white", res = 96, restoreConsole = TRUE )

I need to split a data frame into 3 columns. The column I want to split contains indices of lag (prefix L1 or L2 and suffix 01, 03, 04), station name (shown in the sample data as capitalized G, P and S) and pollutant name. Names with no ?L? prefix or 01/04 suffix are lag 0. Lag 01 is average of lag 0 and 1, and 04 is average of 0 to 4 days. How can one do that in R? I will ignore the other

Dear Experts, I am trying to do a time-stratified case-crossover analysis on air pollution data and number of myocardial infarctions. In order to avoid model selection bias, I started with a simple simulation. I'm still not sure if my simulation is right. But the results I get from the "ts-case-crossover" are much more variable than those from a glm. Is this: a. Due to

Dear Experts, I am trying to do a time-stratified case-crossover analysis on air pollution data and number of myocardial infarctions. In order to avoid model selection bias, I started with a simple simulation. I'm still not sure if my simulation is right. But the results I get from the "ts-case-crossover" are much more variable than those from a glm. Is this: a. Due to the simple

i read a book from WOOD, there's an example which is talking about the pollutant. library(gamair) library(mgcv) y<-gam(death~s(time,bs="cr",k=200)+s(pm10median,bs="cr")+s(so2median,bs="cr")+s(o3median,bs="cr")+s(tmpd,bs="cr"),data=chicago,family=Possion) lag.sum<-function(a,10,11) {n<-length(a) b<-rep(0,n-11) for(i in 0:(11-10))

I can't quite seem to solve a problem subsetting a data frame. Here's a reproducible example. Given a data frame: dat <- data.frame(fac = rep(c("a", "b"), each = 100), value = c(rnorm(130), rep(NA, 70)), other = rnorm(200)) What I want is a new data frame (with the same columns as dat) excluding the top 5% of "value"

Dear R users, I'm trying to get a good x-scale and labels on a plot like the one below. library(lattice) ## make almost a year of hourly data: mydat <- data.frame(dates = Sys.time() + 3600 * (1:7000), y = runif(7000)) ## plot it xyplot(y ~ dates, data = mydat, type = "l") Only one x-label is given (May). I would prefer several because it makes the plot very difficult to

dear R users, my data looks like this PM10 Ref UZ JZ WT RH FT WR 1 10.973195 4.338874 nein Winter Dienstag ja nein West 2 6.381684 2.250446 nein Sommer Sonntag nein ja Süd 3 62.586512 66.304869 ja Sommer Sonntag nein nein Ost 4 5.590101 8.526152 ja Sommer Donnerstag nein nein Nord 5 30.925054 16.073091 nein Winter Sonntag nein

Hola Carlos, Me parece que timePlot genera los gráficos en un formato diferente. Al ejecutar grid.arrange genera el siguiente error: Error in gList(list(list(plot = list(formula = value ~ date | default, : only 'grobs' allowed in "gList" Gracias. Atte. Novvier Uscuchagua De: Carlos Ortega [mailto:cof en qualityexcellence.es] Enviado el: viernes, 16 de junio de 2017 12:38

Hello, Is tail call optimization performed if the ret instruction does not actually follow the tail call? Not according to the documentation, but in examples it seems to work. For example, consider the following definition of Ackerman's function in ML (it has two tail calls): let rec ack x y = if x <= 0 then y + 1 else if y <= 0 then ack (x - 1) 1 else ack (x - 1) (ack x (y -

I appreciate that this is OT, but I'd be grateful for pointers to examples of where Sweave has been used for web-based applications. In particular, examples of where reports/analyses are produced automatically through submission of data to a web-sever. I am mostly interested in situations where pdf reports have been produced rather than, say, a plot/table etc shown on a web page.

Hello, i would like to import this txt file: Giorno;PM10 2006-01-01 10:10;10.3 2006-02-02 20:22;50.3 2006-03-03 23:33;20.1 ......... As it's an irregular time series i use zoo as follow: require(zoo) z <- read.table("c:\\1.csv", sep=";", na.strings="-999", header=TRUE) q <- zoo(z$PM10, strptime(as.character(z$Giorno),"%Y-%m-%d %H:%M")) At this

Dear everyone, I'm encountering an unknown error message when using gamm function: > fitoutput <- gamm(cvd~as.factor(dow)+pm10+s(time,bs="cr",k=15,fx=TRUE)+s(tmean,bs="cr",k=7,fx=TRUE) + ,correlation=corAR1(form=~1|city),family=poisson,random=list(city=~pm10),data=mimp) Maximum number of PQL iterations: 20 iteration 1 iteration 2 iteration 3 iteration 4

Hi Gustav, Try this: lapply(1:length(models),function(i) lapply(models[[i]],function(x) summary(x)$coef[2,]))[[1]] #1st list component [[1]] #??? Estimate?? Std. Error????? z value???? Pr(>|z|) # pm10 #5.999185e-04 1.486195e-04 4.036606e+00 5.423004e-05 #[[2]] #??? Estimate?? Std. Error????? z value???? Pr(>|z|) #ozone #0.0010117294 0.0003792739 2.6675428048 0.0076408155 #[[3]] #???