similar to: chron: parsing dates into a data frame using a forloop

Message: 63 Date: Wed, 26 Jan 2005 04:28:51 +0000 (UTC) From: Gabor Grothendieck <ggrothendieck at myway.com> Subject: Re: [R] chron: parsing dates into a data frame using a forloop To: r-help at stat.math.ethz.ch Message-ID: <loom.20050126T052153-333 at post.gmane.org> Content-Type: text/plain; charset=us-ascii Benjamin M. Osborne <Benjamin.Osborne <at> uvm.edu>

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 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!

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,

Estimados erreros, Estoy intentando entender como calcula el paquete dismo ( https://cran.r-project.org/web/packages/dismo/index.html) un coeficiente de variación. Os pongo un ejemplo: tmin <- c(10,12,14,16,18,20,22,21,19,17,15,12) # temperatura mínima media mensual de un año tmax <- tmin + 5 # temperatura máxima media mensual de un año prec <- c(0,2,10,30,80,160,80,20,40,60,20,0)

Hola, en la misma definici?n de la funci?n: # P15. Precipitation Seasonality(Coefficient of Variation) # the "1 +" is to avoid strange CVs for areas where mean rainfaill is < 1) p[,15] <- apply(prec+1, 1, cv) Un saludo, Jorge On Martes, 19 de Junio de 2018 13:07:27 Marcelino de la Cruz Rot escribi?: > Hola Jaume: > > Si miras el c?digo de biovars() ver?s que la

Hi, I am using mgcv:gam and have developed a model with 5 smoothed predictors and one factor. gam1 <- gam(log.sp~ s(Spr.precip,bs="ts") + s(Win.precip,bs="ts") + s( Spr.Tmin,bs="ts") + s(P.sum.Tmin,bs="ts") + s( Win.Tmax,bs="ts") +factor(site),data=dat3) The total deviance explained = 70.4%. I would like to extract the variance explained

Is there a package in R that can do a variability plot? A variability plot is a kind of categorized dot plot. (If there is a lot of data in each category, box plots are used rather than dot plots.) Usually, the categories are factor level combinations. All the dot plots appear in the same window; below the x-axis a hierarchy of factors shows which dot plot corresponds to which factor-level

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

I have a series of nertCDF files containing global data for a particular variable, e.g. tmin/tmax/precipiation/windspeed/relative humuidity/radiation etc. I get the following information when using *nc_open* function in R: datafile: https://www.dropbox.com/s/xpo7zklcmtm3g5r/gfdl_preci.nc?dl=0 File gfdl_preci.nc (NC_FORMAT_NETCDF4_CLASSIC): 1 variables (excluding dimension variables):

I have a set of modeled climate data recorded at irregular intervals. The format of the data is such that there are monthly measurements for the years 2000, 2020, 2050, 2080, etc. Therefore I have 12 regular records, a skip of some number of years, then 12 more monthly records, another skip, and so on.... I created a dataframe from .txt with the read.table() command. For starters I need

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

Dear useRs, I have the following plot: pos <- c(27/44, 11/32, 8/40, 4/42, 3/40, 4/40, 2/40) tmin <- c(15.8, 12.6, 10.5, 2.4, 5.2, 8.5, 7.9) plot(tmin, pos) I would like to fit an exponential curve to it. How could I be able to do this? Thanks in advance, Rafael. ____________________________________________________________________________________ [[elided Yahoo spam]]

Two questions: 1. Is the order of the dimensions shown what is shown if you look at str(ncin) - I mean shown at the end where it describes the variable and its dimensions? 2. Is you problem how to subset the netcdf file, how to write to the .csv file, or both? -Roy > On Aug 28, 2017, at 2:21 PM, Eeusha Nafi <eshad002 at gmail.com> wrote: > > I have a series of nertCDF files

Hi all, I am trying to run an autologistic model using the function errorsarlm from spdep package. **I built an XY matrix extracting the two colums from matriz** coords1<-matriz[matriz$casos1==1, c(4,5)] coords1<-as.matrix(coords1) **I identify neighbours of region points** nb20<-dnearneigh(coords1,0,20,longlat=TRUE) ** I build a neighbours list with spatial weights**

"It seems therefore that there is no other way than read in individually > 100 weather tables using read.tables., right? Using file.choose() doesn't change the work." Yes. With that many files, file.choose() does not make sense. However, I still do not understand what is the problem with using lapply() on the character vector of file names with read.table() as you did in your

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

Dear all, I have weekly data by city (variable citycode). I would like to take the average of the previous two, three, four weeks (without the current week) of the variable called value. This is what I have tried to compute the average of the two previous weeks; df = df %>% mutate(value.lag1 = lag(value, n = 1)) %>% mutate(value .2.previous = rollapply(data = value.lag1,

Hi R bayesians, I need an advise how to resolve the two different estimates applying a traditional glm (TG) and a bayes glm (BG), and different results depending on the data formats of response data and the prior specs using bayesglm in R. I'm not familiar with bayes estimate and my colleague asked me to look into this because the EPA from France reported a quite different estimates for