similar to: summarizing daily time-series date by month

I have one data frame with a column of dates and I want to fill another data frame with one column of dates, one of years, one of months, one of a unique combination of year and month, and one of days, but R seems to have some problems with this. My initial data frame looks like this (ignore the NAs in the other fields): > mans[1:10,] date loc snow.new prcp tmin snow.dep tmax 1

I have a set of time-series climate data with missing entries. I need to add rows for these missing entries to this data set. The only way I know to do this is unsing a foreloop, but this won't work on a list. I've tried to convert the list to a data frame, but that won't happen, either. I want to fill rows in this table: > newtest[10:15,] yrmos yearmo snow.sum snow.mean

I have a very simple kernel that is generating very very bad code. The basic kernel pseudo-code is as follows: forloop(1 to n) { forloop(0 to j) { A } B } C It is generating very ugly and inefficient code for a vector system similar to the following pseudo-code: if (n > 1) { if (j) { forloop(1 to n) { forloop(0 to j) {

Hi. Am brand new to R and to mailing lists - have never posted anywhere before, so hope I do this right. Am using R 2.9.1 with lattice graphics (just installed, fully up to date). Am doing trellis xyplot with y (emp=employment), x (yearmo=a time measure) and conditioning variable (indf - factor describing industry) -- i.e., (emp ~ yearmo | indf), where all three variables are in a dataframe. The

On Oct 6, 2009, at 4:28 PM, Villmow, Micah wrote: > I have a very simple kernel that is generating very very bad code. > > The basic kernel pseudo-code is as follows: > forloop(1 to n) { > forloop(0 to j) { > A > } > B > } > C > > It is generating very ugly and inefficient code for a vector system > similar to the following pseudo-code: > if (n >

I'm trying to get a data.restore function to work on functions. One thing I can't figure out: how do you construct a function from it's component parts? For example, I can construct a for loop as forloop <- as.call(list(as.name('for'),as.name('i'),1,as.call(list(as.name('junk'))))) which results in for (i in 1) junk() But how do I put that in a

Dear R colleagues, I am trying to plot some geophysical data as a filled contour on a continent map and so far the guidance from the R-help archives has been invaluable. The only bit that still eludes me is the colour key (legend) coming with filled.contour: I prefer to generate my own colour palette, mainly based on the quantiles of tenths of the data in order to capture the whole range (of

Is it possible to give a temporary object a name that varies with each run of a foreloop? For example, I want to fill a matrix every time I run a loop, and I want a new matrix with each run, with an appropriate new name. i.e.: for(i in 1:5){... matrix.i<-some values ...} so that in the end I would have: matrix.1 matrix.2 matrix.3 matrix.4 matrix.5 Thanks, Ben Osborne -- Botany Department

When reading a data set into R using readLines, na.strings="-99.99" is ignored. Is there an equivalent command for readLines? Alternatively, either immediately after reading into R or once the data set has been converted to a data frame, what is the appropriate command (or appropriate use of is.na) to convert my -99.99s to NAs? Thanks, Ben Osborne -- Botany Department University of

1) When adding additional data sets to a plot using "plot" followed by "lines", is there a way to automate the scaling of the axes to allow for all data sets to fit within the plot area? 2) I attempted to solve this by setting xlim=c(min(c(data1,data2,data3)),max(c(data1,data2,data3))) however, there are some NAs and Infs in these data sets, and min(data1) and max(data1) both

Here's a small R program: --------------------------------------------------------------------------- a <- rep(1,10000000) system.time(a <- a + 1) system.time(for (i in 1:10000000) {a[i] <- a[i] + 1}) --------------------------------------------------------------------------- and here's its matlab version:

How can I extract K (number of parameters) from an AIC calculation, both to report K itself and to calculate AICc? I'm aware of the conversion from AIC -> AICc, where AICc = AIC + 2K(K+1)/(n-K-1), but not sure of how K is calculated or how to extract that value from either an AIC or logLik calculation. This is probably more of a basic statistics question than an R question, but I thank

What is the difference between the two R-squareds returned for a linear regression by summary(lm...)? When might one report multiple vs. adjusted R-squared? Thank you, Ben Osborne -- Botany Department University of Vermont 109 Carrigan Drive Burlington, VT 05405 benjamin.osborne at uvm.edu phone: 802-656-0297 fax: 802-656-0440

Does anyone know of a list of functions that R already "knows?" I can't seem to find this anywhere in the help documentation. For example, I want to count the number of occurences of a certain value in a column of a data frame: What do I have to do to tell R to "Count?" Thanks, Ben Osborne -- Botany Department University of Vermont 109 Carrigan Drive Burlington, VT 05405

I'm attempting to do model selection with AIC, using a glm and a lognormal distribution, but: fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian(link="log")) ## gives the same result as either of the following: fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian) fit1<-lm(BA~Year,data=pdat.sp1.65.04) fit1 #Coefficients: #(Intercept) Year2004 # -1.6341

Hello everyone, I am working for a few days already on a basic algorithm, very common in applied agronomy, that aims to determine the degree-days necessary for a given individual to reach a given growth stade. The algorithm (and context) is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and so I implemented my function in R as follows: DD <- function(Tmin, Tmax, Tseuil,

Hi, I have R 2.6.0 with updated lme4 and Matrix packages, and I am trying to fit a nonlinear multilevel model. I get the following error message: Error in nlmer(f ~ grModel(x, w, Tmin, Tmax, Topt, kopt, m) ~ kopt | flat, : gradient attribute of evaluated model must be a numeric matrix and I wonder what this may indicate. The nonlinear model I try to fit is as follows: > grModel

Hello - I am having trouble extracting data from NetCDF data files using RNetCDF. The data files each have 3 dimensions (longitude, latitude, and a date) and 3 variables (latitude, longitude, and a climate variable). Here is some of the output from print.nc for clarity: ----- dimensions: month = UNLIMITED ; // (1368 currently) lat = 3105 ; lon = 7025 ; variables: float

I am trying to run the following code in R on a Linux cluster. I would like to use the full processing power (specifying cores/nodes/memory). The code essentially runs predictions based on a GAM regression and saves the results as a CSV file for multiple sets of data (here I only show two). Is it possible to run this code using HPC packages such as Rmpi/snow/doParallel? Thank you!

On Wed, 22 Nov 2000 13:08:26 +0100, Kurt Hornik wrote: . >>>>> Duncan Murdoch writes: >> I'm trying to get a data.restore function to work on functions. One >> thing I can't figure out: how do you construct a function from it's >> component parts? ... >> forloop <- >>