similar to: Inconsistent results from var.get.nc in RNetCDF

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

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):

Hi, all I have a large number of NetCDF files that I need to average and then put the mean in a new NetCDF file. My problem is that I do this every time for files with different variables, so I do not want to hard-code the variables in the new NetCDF file I creat. does anyone know how I can copy ALL the dimensions and variables from one NetCDF file to another, and just put the mean I calculated as

Hello I am a new user of R . and I ve problem with R and netcdf . I succed installation , I could use all examples . But when I take my netcf it is different . I want to do statistic on this kind of file . 1) first calculate mean . my data is like that through ncdump -h test.nc netcdf test { dimensions: lat = 301 ; lon = 401 ; time = UNLIMITED ; // (80 currently)

Dear Friends, I have been trying to learn how to use the derivative free optimization algorithms implemented in the package RGENOUD by Mebane and Sekhon. However, it does not seem to work for reasons best described as my total ignorance. If anybody has experience using this package, it would be really helpful if you can point out where I'm making a mistake. Thanks in advance Anup Sample

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, First time poster here so let me know if you need any more information. I am trying to run an ordered probit with maximum likelihood model in R with a very simple model (model <- econ3 ~ partyid). Everything looks ok until i try to run the optim() command and that's when I get " Error in rep(1, nrow(x)) : invalid 'times' argument". I had to adapt the code from a 4

Hi, I am using the package ncdf to create netCDF files and I want to mimic the the header of an exiting netCDF file created outside of R. Below is what the existing header looks like (part of it that is different): netcdf ccd1984_05_08 { dimensions: lat = 1974 ; lon = 1894 ; time = UNLIMITED ; // (1 currently) variables: int time(time) ;

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**

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!

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

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,

Dear R-helpers, running a zeroinflated model of the following type: zinb = zeroinfl(count=response ~., x = ~ . - response, z = ~. - response, dist = "negbin", data = t.data, trace = TRUE) generates the following message: Zero-Inflated Count Model Using logit to model zero vs non-zero Using Negative Binomial for counts dependent variable y: Y 0 1 2 3 359 52 7 3 generating

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

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)

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

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

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>

?s 18:59 de 06/11/2024, Sibylle St?ckli escreveu: > Dear Rui > Dear Bert > Many thanks > Solution > filelist <- list.files(path = "O:/Data-Work/2.../Daten_RA-MeteoCH_1990-2021", > pattern='*.dat', all.files= T, full.names= T) > AAR<-read.table(filelist[1]) > It seems therefore that there is no other way than read in individually > 100 > weather

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