similar to: Name assignment in for loop

Hello, helpeRs, I am attempting to reshape (either base R or package reshape) multiple .csv spreadsheets from a very unfortunate wide format to long format. ?Each spreadsheet looks something like this, after being read in to R: toy <- data.frame(year = rep(2007:2008,each = 20), month = rep(1:5,each = 4, length = 40), day = rep(1:2,each = 2,length = 40), hhmm = rep(1100:1101,length = 40),

About time series graphs, I need help to move on: A time series of data directly from a data logger comes in the dat format created below: year<-c(rep(2005,10)) doy<-c(rep(173,5),rep(174,5)) time<-c(15,30,45,100,115,15,30,45,100,115) dat1<-c(0.022128,0.035036,0.051632,0.071916,0.081136,0.07837,0.083902,0. 126314,0.080214,0.117094) dat2<-

Can anybody help me write a code on the following data example, which fills out all NA values by using a linear interpolation with the two closest values? Doy is day of year (%j). Code example: yr<-c(rep(2000,14)) doy<-c(16:29) dat<-c(3.2,NA,NA,NA,NA,NA,NA,5.1,NA,NA,NA,NA,NA,4.6) ta<-cbind(yr,doy,dat) ta yr doy dat [1,] 2000 16 3.2 [2,] 2000 17 NA [3,] 2000 18 NA

Hello, I am getting output from anova() and summary(aov()) that depends on the order of the factors in the fitted model object, and this has me baffled. I see this dependency with the data.frame below but not with an example (table 6.4) from Montgomery's DOE book. This is with R 1.3.0 on Debian GNU-Linux. Where have I gone wrong? > centerpts run sample CH50mg 1 day1 dev126 0.56 2

Dear R community, I have a fairly large file with variables in rows. Every variable (thousands) needs to be regressed on a reference variable. The file is too big to load into R (or R gets too slow having done it) and I do now read in line by line with "scan" (see below) and write the results to out. Although improved, this is still very slow... Can someone please help me and suggest

Hello, helpeRs, I have a vector of numbers from 1-365 (days of the year) that I would like to convert to a date. There are no NA's and no missing values. I did not insert leading zero's for numbers less than 100. Using the syntax: dat$doy.1 <- as.numeric(format(dat$doy, "%j" )) I get the following error message: Error in prettyNum(.Internal(format(x, trim, digits,

I would like to include this in a package. The S3 methods on R CMD check says * checking S3 generic/method consistency ... WARNING window: function(x, ...) window.chron: function(data, day1, hour1, day2, hour2, ...) See section 'Generic functions and methods' of the 'Writing R Extensions' manual. I have looked and can not figure it out. This function is for convience. What

Hi, I have a data.frame SAMPLES with columns: Site Site# Season Day1 Day2 Day3 Day1, Day2, Day3 are class "Date", the other columns are numeric or factor. I have a date "mydate" that may or may not be listed in my data.frame and I need to find that out. If "mydate" is there, I want to get the number of the data.frame row where it occurs.

Hello all, I have two comboboxen, comboA is popultaed when :controller/list is retrieved first time. When comboA is selected, I want to auto-populate comboB (modelB belongs_to modelA). The population of tableC (modelC belongs_to modelB and belongs_to modelA) should not populate until a "GO" button is clicked (link_to with submit). Help? I need an example of how to filter the post

Dear group, Here is my environment : > ls() [1] "l" "PLglobal" "Pos100415" "Pos100416" "Pos100419" "Pos100420" "position" "select" "Trad100415" "Trad100416" "Trad100419" "Trad100420" "trade" "y" With objects : > l [1]

HI all, raw_urine = read.table("Z:\\bruce.9.3.09.sample.stability.analysis\\urine\\mz.spot.sam.dat.new", header = TRUE ) pvalue = read.table("Z:\\bruce.9.3.09.sample.stability.analysis\\urine\\all.urine.features.t.test.result", header = TRUE ) library(compositions) p = function(a,b){ y = pvalue[,a] if(y<0.01){ index = which(y, arr.ind=TRUE) day1 = raw_urine[index,3:7] day2 =

Can someone help me with the proper usage of the reshape function? Let's say I have a dataset with columns like this (wide format): Id Sex Group Test Day1 Day 2 Day 3... And I want to transpose this into something like this (thin): Id Sex Group Test Time Where the new column labeled time contains all the time variables (Day 1, Day 2, Day 3...) that were in the wide

Hello gurus, I have a dataframe containing two groups viz., 'control' and 'case', each of these groups contains longitudinal data for 100 subjects. I have to plot all these subjects on a single chart and then put a regression line for each of the group for all the subjects. I have written a function to do the chart grpcharts<-function (dat, group,group2,molecule,cutoff){

Dear List, I apologize in advance if this is silly. I tried to replicate an analysis I did previously in SPSS using R, and was surprised to find different results. So my question is: shouldn't the following SPSS syntax REGRESSION DEPENDENT INC89 /METHOD=ENTER hiedyrs experien SE93rec. Yeld the same results of the following R command modelB<-lm(INC89~HIEDYRS+EXPERIEN+SE93REC) I

Hi everyone I was using spline to interpolate single or two consecutive missing data points in time series. However, when it comes to longer gaps in the data the spline function generate new data for both my known and unknown data (see below). Aside from not understanding why this happens, I thought thought I might try function "aspline" in library (akima). However, I cannot install or

I use model comparison with glms without mixed effects with anova(modelA,modelB), with mixed effects glm (glmmPQL), this doesn't work. Is there a way to compare model fits with glmmPQL's? Paula M. den Hartog Behavioural Biology Institute of Biology Leiden Leiden University [[alternative HTML version deleted]]

Dear all, I have following two list object, both are basically collection of matrices : dat1 <- matrix(rnorm(25*6), ncol=6) dat1 <- split(dat1, seq(5,25,by=5)) dat1 <- lapply(dat1, matrix, ncol=6) dat2 <- matrix(rnorm(25*4), ncol=4) dat2 <- split(dat2, seq(5,25,by=5)) dat2 <- lapply(dat2, matrix, ncol=4) Now I want to replace last 4 columns of each matrix at "dat1"

This patch adds support for symbol versions. It is based on what libvirt does. The generated syms file looks like: LIBNBD_1.0 { global: nbd_...; nbd_...; local: *; }; In a future stable 1.2 release, new symbols would go into a new section which would look like this: LIBNBD_1.2 { global: nbd_new_symbol; nbd_another_new_symbol; local: *; } LIBNBD_1.0; In my testing the

# Hi there, # I am trying to apply a function over a moving-window for a large number of multivariate time-series that are grouped in a nested set of factors. I have spent a few days searching for solutions with no luck, so any suggestions are much appreciated. # The data I have are for the abundance dynamics of multiple species observed in multiple fixed plots at multiple sites. (I total I

Hello and thanks for helping. #some data L3 <- LETTERS[1:3] dat1 <- data.frame(cbind(x=1, y=rep(1:3,2), fac=sample(L3, 6, replace=TRUE))) #When x==1 and y==1 I want to replace the 1 values with NA #I can select the rows I want: dat2<-subset(dat1,x==1 & y==1) #replace the 1 with NA dat2$x<-rep(NA,nrow(dat2) dat2$y<-rep(NA,nrow(dat2) #select the other rows and rbind