similar to: Maximum value of two columns

Hi, Am I hitting some limit in match? Consider the following example: > tst<-seq(100,125,by=.2)%in%seq(0,800,by=.1) > sum(tst) [1] 76 > seq(100,125,by=.2) [1] 100.0 100.2 100.4 100.6 100.8 101.0 101.2 101.4 101.6 101.8 102.0 102.2 [13] 102.4 102.6 102.8 103.0 103.2 103.4 103.6 103.8 104.0 104.2 104.4 104.6 [25] 104.8 105.0 105.2 105.4 105.6 105.8 106.0 106.2 106.4 106.6 106.8

Hi, Am I hitting some limit in match? Consider the following example: > tst<-seq(100,125,by=.2)%in%seq(0,800,by=.1) > sum(tst) [1] 76 > seq(100,125,by=.2) [1] 100.0 100.2 100.4 100.6 100.8 101.0 101.2 101.4 101.6 101.8 102.0 102.2 [13] 102.4 102.6 102.8 103.0 103.2 103.4 103.6 103.8 104.0 104.2 104.4 104.6 [25] 104.8 105.0 105.2 105.4 105.6 105.8 106.0 106.2 106.4 106.6 106.8

HI: I need ideas on how to make this code shorter (maybe with a second loop?). The code as it is works, but in this case I only have 14 samples, but it will become insane with more, so I need a way to make it more automatic. The problem is that the output from ts1, ts2, and so on is a vector with more than one value, so I do not know how to solve this. Thanks Prenewbie The code is the

Very much a rookie at R, and have only recently started using it again so pardon the simple question. I am trying to produce a box plot from one data set and then overlay a line plot from another data set. The box plot data set is made up of 20 sets of 30 data points, or 600 total data points. The line has only 30 total data points. The box plot is plotting fine, but for some reason, the line plot

Hello, I'm trying to adjust a non linear model in which the biological response variable (ratio of germinated fungus spores) is dependent on 2 covariates (temperature and time). The response to temperature is modeled by a kind of beta function with 2 parameters (optimal and maximum temperatures) and the time function is a 2-parameter Weibull. Adjustments with nls or gnls work, but I need to

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

Dear all, I am trying to create a vector name, for example tmax.195012 from tmax., 1950 and 12. Obviously I don't wish to simply type it because the 3 name components are changing in each iteration within a loop. Is there any way of concatenating those 3 components (which are a mixture of numbers and letters)? Thanks for reading, Panos

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,

Hello, I am an R newbie, trying to use lsoda to solve standard Lotka-Volterra competition equations. My question is: how do I pass a parameter that varies with time, like say, phix <- 0.7 + runif(tmax) in the example below. # defining function lotvol <- function(t,n,p){ x <- n[1]; y <- n[2] rx <- p["rx"]; ry <- p["ry"] Kx <-

Dear all, I have a data similar to this: myframe<- data.frame (ID=c("Ernie", "Ernie","Ernie","Ernie"), Timestamp=c("24.09.2012 08:00", "24.09.2012 09:00", "24.09.2012 10:00", "25.09.2012 10:00"), Longitude=c("8.481","8.482","8.483","8.481"),

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!

Dear all Im new in R I have a necdf data set that I want to plot : this is my data set [1] "file Tmax.DJF.daily.1981_1999.echama2.nc has 4 dimensions:" [1] "longitude Size: 127" [1] "latitude Size: 110" [1] "ht Size: 1" [1] "t Size: 1680" [1] "------------------------" [1] "file Tmax.DJF.daily.1981_1999.echama2.nc has 1

Greetings all! A recent news item got me thinking that a problem stated therein could provide a teasing little exercise in R programming. http://www.bbc.co.uk/news/uk-england-cambridgeshire-17680326 Cambridge University hosts first European 'maths Olympiad' for girls The first European girls-only "mathematical Olympiad" competition is being hosted by Cambridge

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)

Thank you for providing the example code... for the request of running it multiple times it would have helped if you could have confirmed that the example ran through without errors... there were a lot of mistakes in it. Look into using the reprex package to check your example next time. I don't do this kind of analysis... I really don't know what to expect from the functions. The

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

[answers inline] On 18 August 2017 at 20:08, Dagmar <Ramgad82 at gmx.net> wrote: > > myframe<- data.frame (ID=c("Ernie", "Ernie","Ernie","Ernie"), > Timestamp=c("24.09.2012 08:00", "24.09.2012 09:00", "24.09.2012 10:00", > "25.09.2012 10:00"),

R 2.10 Windows 7 I am trying to plot three graphs on top of each other. I need to have the axises perfectly aligned. For some reason the ticks on the y axes are slightly off so they do not perfectly align. Can someone tell me how I can get the to overlay each other perfectly? I thought the yaxp parameter would solve my problem, but it does not. My data and code follows: >

Colleagues I want to convert a 10x2 array: # create a 10x2 matrix. datavals <- matrix(nrow=10,ncol=2) datavals[,] <- rep(c(1,2),10)+c(rnorm(10),rnorm(10)) datavals into a 10x3 array, ThreeDArray, dim(10,2,10). The values storede in ThreeDArray's first dimensions will be the data stored in datavalues. ThreeDArray[i,,] <- datavals[i,] The values storede in ThreeDArray's second

I have a generalized linear model to solve. I used package "geepack". When I use the correlation structure "unstructured", I get a messeage that- R GUI front-end has stopped working. Why this happens? What is the solution? The r codes are as follows: a<-read.table("d:/bmt.txt",header=T")