similar to: accessing variables inside a function, inside a loop

hello list! I'm sorry, I just stumbled over this strange behaviour (at least I am not able to explain the behaviour, therefore I assume it to be a strange behaviour): attach(water) # I know, this is not recommended names(water[3:10]) [1] "temp" "pH" "DO" "BOD" "COD" "no3" "no2" "po4" for (i in

Hello. I am wondering why I am getting NA for all in cors=sapply(pred,cor,y=resp). I suppose that each column in pred has NAs in them. Is there some way to fix this? Thanks > str(pred) 'data.frame':   200 obs. of  13 variables:  $ mnO2: num  9.8 8 11.4 4.8 9 13.1 10.3 10.6 3.4 9.9 ...  $ Cl  : num  60.8 57.8 40 77.4 55.4 ...  $ NO3 : num  6.24 1.29 5.33 2.3 10.42 ...  $ NH4 : num  578

On Sun, 2009-07-26 at 13:17 +0200, Poersching wrote: > stvienna wiener schrieb: > > Hi all, > > > > I am plotting a financial time series, but I need a more detailed X-Axis. > > > > Example: > > x <- zoo(rnorm(1:6000), as.Date("1992-11-11")+c(1:6000)) > > plot(x) > > > > The X-Axis is labeled "1995", "2000"

hello dear list! as I am currently helping someone with their statistical analysis of a count survey, I stumbled upon a very basic question upon model optimization: when fitting a model like: model<-lmer(abundance~(x+y+z)^3,family=poisson,...) in which x,y,z are continuous abiotic parameters such as po4 concentration, no2-concentration, which terms / interaction terms would you recommend

Good day, I read some data from a PostgreSQL database by a following script: library(Rdbi) library(RdbiPgSQL) # conn becomes an object which contains the DB connection: conn <- dbConnect(PgSQL(), host="localhost", dbname="BVS", user="postgres", password = "*******") query_duj_kal <- dbSendQuery(conn, "select zdroj as well, cas as date, fe2,

Greetings, I am new to R and am having trouble with parsing a file with the following characteristics: * Individual results for a single sample are written to multiple lines. * First 16 columns are constant from sample to sample. * Remaining 10 need to be matched up (cross-tabbed?) o (the exact contents for the remaining 10 vary from sample to sample, as indicated in

I have a data frame with 1 factor, one date, and 37 numeric values: str(waterchem) 'data.frame': 3525 obs. of 39 variables: site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1 1 1 1 ... $ sampdate : Date, format: "2007-12-12" "2008-03-15" ... $ CO3 : num 1 1 6.7 1 1 1 1 1 1 1 ... $ HCO3 : num 231 228 118 246

Hello, I'm a beginner with R and it's the first time I'm using the R-help list... I hope I'm in the right place, if not: Sorry!! I need to do non linear regressions on a data set which columns are: "river.name" "Portata" "PTG.P" "PO4.P" "NT.N" "NH4.N" "NO3.N" "BOD5" "SiO2"

Dear list, I am using R 2.1.1 on a Fedora 3 Linux, 32 bit PC. If I compute the aggregated mean and the standard deviation I get standard deviation values for factors where the mean was not computed. It seems to me that this is somehow related to the NA values. But I don't quite understand what is going wrong? Could it be related to the data import already? Some of the imported data got the

Hello. Does anyone know of an existing function that takes a list in the form of: Plot1 Species1 Abundance1 Plot1 Species2 Abundance2 Plot2 Species1 Abundance1 Plot2 Species3 Abundance3 . . . PlotN SpeciesN AbundanceN and translates into a matrix in the form of Species1 Species2.... SpeciesN Plot1 Abundance1 Abundance2... AbundanceN Plot2 Abundance1

I am not sure if this is an R-users question, but since most of you here are statisticians, I decided to give it a shot. I am using the lm() function in R to fit a dependent variable to a set of 3 to 5 independent variables. For this, I used the following commands: >model1<-lm(function=PBW~SO4+NO3+NH4) Coefficients: (Intercept) SO4 NO3 NH4 0.01323 0.01968

Hi R forum, Each row of my data (below) show a new contact event between animals. In order to ultimately look at the patterns of intervals between contacts, I need to calculate a contact end time. The contact starts at the date and time shown in V4 and V5, and lasts for the duration shown IN SECONDS in V6: > data2<- read.csv(file=file.choose(), header=F, sep=" ") >

Good day, I'm trying to get more time series in one plot. As there are bigger differences in values of variables I need logaritmic y axis. The code I use is the following: nvz_3_data <- read.csv('/home/tomas/R_outputs/nvz_3.csv') date <- (nvz_3_data$date) NO3 <- (nvz_3_data$NO3) NH4 <- (nvz_3_data$NH4) date_p <- as.POSIXct(date, "CET") par(mfrow=c(2,1), ylog

Dear list users, I have trouble with covariance analysis. I measured nitrate concentrations in the soil (NO3) and the percentage of legumes (LEG, continuous), affected by 2 different CO2 concentrations (CO2, discrete). I suspect that CO2 has an effect on LEG and NO3, but also that LEG has an effect on NO3, so this is the formula I wrote to test this: NO3 ~ CO2 + LEG + CO2:LEG Will LEG be

dear listers, I use gam (from mgcv) for evaluation of shape and strength of relationships between a response variable and several predictors. How can I interpret the 'F' values viven in the GAM summary? Is it appropriate to treat them in a similar manner as the T-statistics in a linear model, i.e. larger values mean that this variable has a stronger impact than a variable with smaller F?

Hi Second question in a day, i'm beginnning to feel incompetent... This time i'm having a weird problem, i'm importing the next data base: >car<-read.csv2("Historicos.csv") 'data.frame': 1818 obs. of 6 variables: $ Dpto : Factor w/ 11 levels "ANTIOQUIA","ATL?NTICO",..: 2 2 2 2 2 1 1 1 1 5 ... $ Rio : Factor w/ 43 levels

Hi, my name is Luis, and I have a problem with a dataset. Its name is algae and count the collection of data in a lake and respective proliferation of algae. The parameters that it has are: "mxPH", "mnO2", "Cl", "NO3" "NH4", "oPO4", "PO4", "Chla" and "a1" all numerics. a1 - algae1 If I try to do SVM with

Dear R-users, I am a newbie to this site and a relative new-comer to S/R, so please tread lightly, for you tread... There have been several posting relating to problems with augPred() from the nlme library. Here is a "fix" for one of these problems which may lie at the root of others. In my case the problem with augPred() lay in gsummary(), which augPred() uses, causing it to fail.

Hi Dennis, SOLVED!!! My thanks to both you, John, and others who chimed in. Took a little more digging before finally working, but it is working! Here's a little more of what I did and the ultimate resolutions: I installed the reshape2 library from CRAN. Executed > (.packages()) [1] "reshape2" "stats" "graphics" "grDevices"

Hi everyone, I recently bought a qnap TS-209Pro [www.qnap.com]. This embeds samba 3.0.23d.I configured it to connect to our Active Directory, but as soon as I set winbind enum users and winbind enum groups to "yes" in the /etc/smb.conf file, winbindd uses 100% of CPU. I've googled the problem and found a lot of problems, less solutions... Does anybody have a clue on this ? I have