similar to: How to do a time-stratified case-crossover analysis for air pollution data? Unformatted text-version, with an additional note

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

I got a strange problem with init.d scripts on a fully updated (as of today) fresh install of 5.5 x64. I've written a script, /etc/init.d/Fast that starts a fairly large and slow commercial application, by calling that applications control binary to do the actual work. I "registered" the script, via chkconfig --add Fast, and the symlinks are in the expected places. [root at

The attached patch is an updated version of my quota-rquotad patch for the quota plugin. Like quota-fs, it only does quota reporting, not enforcing or changing. It also only works on FreeBSD, and possibly other *BSD's. It lacks any and all configure-time tests to see if RPC is even supported, and hardcodes the (Free)BSD way of getting at the NFS server of an NFS mount. I'm mostly mailing

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

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

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]] #???

SunOS fluke 5.8 Generic_108528-07 sun4u sparc SUNW,Ultra-Enterprise R-1.4.0 Running from the command line R CMD check chlib results in the log file 00check.log: * using log directory `/home/woodstock/hoffmann/R/Sources/chlib.Rcheck' * checking for file `chlib/DESCRIPTION' ... OK * checking package directory ... OK * checking for sufficient/correct file permissions ... WARNING *

Hi R people, I want to write some functions to automate the plotting of some expressions that use some of the plotmath capabilities. An example is a string supplied to a plot call such as: plot(1, 1, ylab = "pm10 (ug/m3)") This should actually appear like: plot(1, 1, ylab = expression("PM"[10] * " (" * mu * "g m" ^-3 * ")")) i.e. pollutant

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

I am analyzing particulate matter data (PM10) on a small data set (147 observations). I fitted a semi-parametric model and am worried about overfitting. How can one check for model fit in GAM? Jean G. Orelien

Dear R users: In the example of meta-analysis (cochrane, package rmeta), I can not found the p-value of Test for overall effect, and some other indices (Z, I, weight and et al). How can I get the these indices listed? > library(rmeta) > data(cochrane) > cochrane name ev.trt n.trt ev.ctrl n.ctrl 1 Auckland 36 532 60 538 2 Block 1 69 5

SunOS fluke 5.8 Generic_108528-07 sun4u sparc SUNW,Ultra-Enterprise R-1.4.0 Running from the command line R CMD check chlib results in the log file 00check.log: * using log directory `/home/woodstock/hoffmann/R/Sources/chlib.Rcheck' * checking for file `chlib/DESCRIPTION' ... OK * checking package directory ... OK * checking for sufficient/correct file permissions ... WARNING *

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

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

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))

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

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 nein Ost 6

Hello everybody Is there a way to output data into a file like the unformatted, direct fortran files? That's the kind that can be opened with: open(30, file='file', format='unformatted', access='direct', rec=1000, convert='big endian') Thank you in advance Kostas Douvis