similar to: Help on zoo and datetime series

hi, i'm trying to perform a clustering on a big dataframe the code is this: print("load required R packages") require(spgrass6) require(cluster) gmeta6 <- gmeta6() print("read in our 7 raster files from GRASS") x <- readFLOAT6sp(c ("er","crosc","longc","slope","profc","minic","maxic"))

hi to all, frustated for this error, to day i buy a 1 GB memory slot for my laptop now it have 1,28GB instead the old 512, but i've the same error :-( damn!damn!....how can i do? repeat for a little area (about 20X20 km and res=20m) it work fine! have you any suggestion? is ther a method for look if this error depend from my ram or other....? thanks foe any suggestion! i need your help.

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

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]] #???

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

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

I am trying to sort a list and the data is obiously not in the right format. I am trying: x <- list() x[["A"]] <- 1 x[["B"]] <- 2 order(x) But am getting: Error in order(x) : unimplemented type 'list' in 'orderVector1' How should I change the list so that it can be sorted? What kinds of objects (classes of objects) can be sorted? Thank you. Kevin

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 all, If I have a data frame x<-data.frame(x1=c(1,7),x2=c(4,6),x3=c(8,2)): x1 x2 x3 1 4 8 7 6 2 I want to sort the whole data and get this: x1 1 x3 2 x2 4 x2 6 x1 7 x3 8 If I do sort(X), R reports: Error in order(list(x1 = c(1, 7), x2 = c(4, 6), x3 = c(8, 2)), decreasing = FALSE) : unimplemented type 'list' in 'orderVector1' The only way

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))

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

In the text file pressione2008.csv I have the following "Data","MAX","MIN","Note" "07-01-2008 08:00:00", 135, 90, "Eccessi feste, inizio dieta" "07-01-2008 18:00:00", 135, 85, "" "08-01-2008 08:00:00", 125, 75, "" which is a collection of blood pressure data at different time of the day. I would

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

If anyone can assist with this problem you have my great thanks: I am trying to establish and plot confidence intervals on a bootstrapped function. I have a more complicated function that has no problems with determining the confidence intervals using the quantile command. This is outside the bootstrap portion of the code that is working fine it is just determining everything for the more

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

I guess we could make it do the equivalent of do.call(order, df). On Mon, May 18, 2020 at 8:32 AM Rui Barradas <ruipbarradas at sapo.pt> wrote: > > Hello, > > There is a result with lists? I am getting > > > order(list(letters, 1:26)) > #Error in order(list(letters, 1:26)) : > # unimplemented type 'list' in 'orderVector1' > >

Full_Name: Murray Smith Version: 2.2.1 OS: Windows XP Submission from: (NULL) (202.36.29.1) order() will not allow a complex vector for its first argument. This contrasts with sort() which will happily sort a complex vector. While this may not be regarded as a bug by some, it is annoying for anyone who makes frequent use of complex numbers. The problem occured in the Windows version 2.2.1 of

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

Dear Sir, In the functions orderVector1, orderVector1l (R-3.5.2/src/main/sort.c) there are two loops concerning nalast (lines 1096, 1105). I am not sure about the possibility of redefining them, so this function should be a little faster. The first one (line 1096) can be included in the previous 'switch' block (line 1079) (see below). And if you rewrite/duplicate this 'switch'