search for: jday

Dear All, I have several sets of data such as this: year jday avg_m3s 1 1960 1 4.262307 2 1960 2 4.242308 3 1960 3 4.216923 4 1960 4 4.185385 5 1960 5 4.151538 6 1960 6 4.133846 ... There is a value for each day of multiple years. In this particular data set it goes up to 1974. I am am looking to obtain the minimum and maximum values for...

...proportion > # { > # z <- qnorm(1-alpha/2) > # merror <- z * sqrt(phat*(1-phat)/M) # M is (Monte Carlo) sample size > # merror > # } > > #Bring in temp file > > temper <- scan("temp.dat", na.strings = ".", list(Day=0, jday=0, Temp=0)) Read 366 records > > Day<-temper$Day ; jday<-temper$jday ; Temp<-temper$Temp ; > > temp<- cbind (Day, jday, Temp) > #Day = number of days modelled, jday=julian day, Temp = daily avg. temp. > #temp [,2] > > Vc<-(CTM-(temp[,3]))/(CTM-CTO) &g...

...A, -48L), class = "data.frame") given that, my objective is to create a new variable accounting for the julian day (i.e. the number of consecutive days elapsed from a fixed origin date) and these are (among many others) my (most) unsuccessful attempts? library(chron) #not working! test$jday<-julian(test$date, origin=as.POSIXct(test$date)) #not working! test$jday<-julian(test$date, origin=test$date) #not working! test$jday <-julian(as.Date(test$date, "%m"), as.Date(test$date, "%d"), as.Date(test$date, "%Y"),...

...Manuel. ________________________________ (1) F77 code subroutine weathersel(GRD,YR,SWJD,HRVJD) C ========================================== C ---------------------------------------------------------- C ---------------------------------------------------------- C INTEGER :: GRID,YEAR,JDAY,A,B,C,D REAL :: LAT,LONG,MINT,MAXT,TEMP REAL :: PREC,WIND,RAD,RH,DELTA,ET C----------------------------------------------------------- C ** Identifying the variables C A=GRD B=YR C=SWJD D=HRVJD C C------------------------------------------------------------- C *...

...function(phat,M,alpha) # (1-alpha)*100% merror for a proportion # { # z <- qnorm(1-alpha/2) # merror <- z * sqrt(phat*(1-phat)/M) # M is (Monte Carlo) sample size # merror # } #Bring in temp file temper <- scan("temp.dat", na.strings = ".", list(Day=0, jday=0, Temp=0)) Day<-temper$Day ; jday<-temper$jday ; Temp<-temper$Temp ; temp<- cbind (Day, jday, Temp) #Day = number of days modelled, jday=julian day, Temp = daily avg. temp. #temp [,2] Vc<-(CTM-(temp[,3]))/(CTM-CTO) Vr<-(RTM-(temp[,3]))/(RTM-RTO) comp<- cbind (Day, jday, Te...

...nt to do, > since there are no "B" > plot(a ~ b, d) # yuk! > > ## Section 2: Why is this important? Consider another realistic > example of [synthetic] daily temperature > > temp <- 5 - 10*cos(1:365*2*pi/365) + rnorm(365)*3 > d1 <- data.frame(year=2005, jday=1:365, date=NA, month=NA, temp) # > jday is Julian day [1,365] > d1$date <- as.Date(paste(d1$year, d1$jday), "%Y %j") > d1$month <- factor(months(d1$date,TRUE), levels=month.abb) > plot(temp ~ month, d1) # perfect, in a perfect meteorological world > > d2 <-...

...b="B")) # which I don't want to do, since there are no "B" plot(a ~ b, d) # yuk! ## Section 2: Why is this important? Consider another realistic example of [synthetic] daily temperature temp <- 5 - 10*cos(1:365*2*pi/365) + rnorm(365)*3 d1 <- data.frame(year=2005, jday=1:365, date=NA, month=NA, temp) # jday is Julian day [1,365] d1$date <- as.Date(paste(d1$year, d1$jday), "%Y %j") d1$month <- factor(months(d1$date,TRUE), levels=month.abb) plot(temp ~ month, d1) # perfect, in a perfect meteorological world d2 <- d1[!d1$month %in% c("Mar&...

...---------------- library(''RPostgreSQL'') drv <- dbDriver("PostgreSQL") dbh <- dbConnect(drv,user="…",password="…",dbname="…",host="…") sql <- "select id, date, lon, lat, date_trunc(''day'' , date) as jday, extract(''hour'' from date) as hour, extract(''year'' from date) as year from observations where pt = 6 and date >= ''1990-01-01'' and date < ''1995-01-01'' and lon > 180 and lon < 290 and lat > -30 and lat < 30 and...

Sorry for asking this but I am keen to get on and build an app based on RoR and have had a look around at FAQa and the like with no immediate sucess. What I am looking for is an explainantion of the rules/requirements for table/index/coulumn names with RoR. RoR appears to have a set of expected naming conventions which it would appear you can over ride but it would seems a hell of a lot

Dear All, I am being told that R can process text files and strings as well as Perl (and is certainly more elegant). Being an R neophyte I need a little boost to get started. I have a little benchmark program in Perl that reads a delimited file, creates an inverted table and spits the file out again in key sorted order. It's just a few lines of Perl (see below). Can someone write the

Dear All, Does anyone use S or R for statistical natural language processing (NLP)? All I have found so far is a package called EMU (http://www.shlrc.mq.edu.au/emu/emu-splus.shtml) which is a speech wave-form processing package. What I'm looking for are routines to support text processing, text categorization, word sense disambiguation, text understanding etc. In particular, I would

...URL `http://cran.r-project.org/bin/windows/contrib/PACKAGES' unable to connect to 'cran.r-project.org'. Error in download.file(url = paste(contriburl, "PACKAGES", sep = "/"), : cannot open URL `http://cran.r-project.org/bin/windows/contrib/PACKAGES' -jday At 11:48 AM 9/6/2002 +0200, you wrote: >"Marc Schwartz" <mschwartz at medanalytics.com> writes: > > > Is anyone else having trouble accessing the main R Project and CRAN > > sites? I had not seen any other posts about it. > > > > I noted the problem t...

I was wondering if R had a data mining componant and how i could get it. If not do you know anyone who is developing a datamining "plug in" for R Phillip Goodreid -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe"

Dear R-guRus: I have a problem with the format of my data in R. Let's say I have a HUGE text table which consists of columns of numerical data, separated by tabs, but in some places rows of text (error messages, etc) are inserted in between rows of numerical data. Because the data file is so huge and because I have thousands of these files, it's unpractical to try and go thru these

Hello, This is not exactly an R question, but I suspect that there is an R procedure that does what I am calling (for lack of a better name) "histogram ranking". I'm trying to evaluate a set of regression features by segregating by target class and comparing the feature histograms. My idea is that if the histograms are the same for two different classes then there is no