similar to: Subsampling-oversampling from a data frame

R-help readers, I''m having a problem with an R script (see below), which regularly generates the error message, Error in start:(start + (sample.length - 1)) : NA/NaN argument , for which I am unsure of the cause. In essence, the script (below) generates the start and end points for random subsamples from along a vector (in reality a transect (of a given length,

Hello R-users, I am trying to obtain Type III SS for an ANOVA with subsampling. My design is slightly unbalanced with either 3 or 4 subsamples per replicate. The basic aov model would be: fit <- aov(y~x+Error(subsample)) But this gives Type I SS and not Type III. But, using the drop() option: drop1(fit, test="F") I get an error message: "Error in

*Dear R community* * * *I have two questions on data subsample manipulation. I am starting to use R again after a long brake and feel a bit rusty.* * * *I want to select a subsample of data for males and females separately* * * library(foreign) Datatemp <- read.spss("H:/Skjol/Data/HL/t1and2b.sav", use.value.labels = F) > table(Datatemp$sex) 1 2 3049 3702

hi, I would like to subsample the array c(1:200) at random into ten subsamples v1,v2,...,v10. I tried with to go progressively like this: > x<-c(1:200) > v1<-sample(x,20) > y<-x[-v1] > v2<-sample(y,20) and then I want to do: >x<-y[-v2] Error: subscript out of bounds.

Hello, How can I randomly sample individuals within a sites from a site (row) X species abundance (column) data frame or matrix? As an example, the matrix "abund2" made below. ##### (sorry, Im a newbie and this is the only way I know to get an example on here) abund1 <- c(150, 300, 0, 360, 150, 300, 0, 240, 150, 0, 60, 0, 150, 0, 540, 0, 0, 300, 0, 240, 300, 300,

G'day R-helpers, I want to subsample rows of a large table based on the value in its first column. Of all rows sharing the same value in the first column I want to RANDOMLY extract only one. Thanks in advance, Achim example input 1 15 34 1 4 66 1 24 65 2 23 47 2 9 36 3 58 9 3 38 64 3 12 64 3 4 15 4 1 88 4 23 90 desired output 1 4 66 2 23 47 3 12 64 4 1 88

Hi I have an umbalanced data set where I want to predict a binary variable Y. I want to do an under sampling by keeping all the 1 and taking just some of the 0 such as I'll have 90% of 0 and 10% of 1. Can u help me do that Thank u [[alternative HTML version deleted]]

Hi all, I am trying to predict a target variable that takes values 0 or 1 using the rpart command. In my initial dataset I have few positive observations of the target variable; therefore I have oversampled the rare event by a multiple of 6 (i.e. from 762 to 4572). However, in my results, I end up with a number of positives in one of the terminal nodes that is not divisible by 6. As I have the

Hi: I need some help with the legend. I got 14 samples(Muestreo) and I am trying to plot a smooth line for each sample. I am able to accomplish that but the problem is that the legend only displays every other sample. How can I force the legend to show all of my Muestreos? Thanks in advance. fish_ByMuestreo <- structure(list(data = structure(list(SampleDate = structure(c(3L, 3L, 3L, 3L,

I am attempting to graph 12 months of temperatures, delineate the months with a vline and place the names of the months at the top of the graph. So far I have gotten everything to work except the names, despite getting a similar graph to work yesterday the day before yesterday with Baptise A's help. Can anyone suggest what I am doing wrong. Data set is below code. Thanks. Code

Dear r-users, I would like to construct 3-day moving average for block maxima series. I tried this: bmthree <- lapply(split(dt, dt$Year), function(x) max(sapply(1:(nrow(x)-2), function(i) with(x, mean(Amount[i:(i+2)],na.rm=TRUE))))) bmthree and got the following output. $`1971` [1] 70.81667 $`1972` [1] 68.94553 $`1973` [1] 102.7236 $`1974` [1] 73.6625 $`1975` [1]

Hi I am very new to R, I am attempting to produce a monthly boxplot with the following fish thermal telemetry data: ID Temp Date.Time Month.Year Month Week Shortdate 1 1734 4.4140 04/05/2010 11:56 05,2010 May 19 04/05/2010 2 1734 4.1002 04/05/2010 12:06 05,2010 May 19 04/05/2010 3 1734 3.9433 04/05/2010 12:09 05,2010 May 19 04/05/2010 4 1734 3.6295

I had a problem annotating a graph last year ( see http://n4.nabble.com/Putting-names-on-a-ggplot-td907158.html#a907158 for the discussion) Stefan (smu) provided a solution using annotate(). However I apparently did not update the graph file and,now, when I go back to the thread and try to use Stefan's solution it does not seem to work although I am sure that it did then. The problem

I'm creating a lattice barchart based off a pretty complicated data structure. The barchart comes out quite nice ( thanks to lattice ) but the problem is that the horizontal axis comes out all scrunched because the barchart doesn't know that the intervals of Var.1 are really "associated" with the conditioning variable Var.2. Therefore, all the intervals of Var.1 are put on

I would like to organize my data as follows: I have a table that contains various data, and the numbers represent a level of similarity between these data, eg RF00013 has 100% similarity with the data RF00014. I would leave my table as a heatmap where darker colors represent higher similarity, and the lighter colors represent less level of similarity. I'm using version 2.11 of R. these

I have a dataframe df with columns x, y, and height. I want to create a heatmap-like plot that creates a grid of x by y, and then color codes the grid depending on the value of height. Is there a ggplot2 object to do this? I'm able to easily do this in Excel with pivot tables and conditional formatting so I'm including an image that is close to the output I want. I want to be able to

Hi all, I have the following data and I have a histogram for mms like ggplot(hist,aes(x=hist$mms))+ geom_histogram(binwidth=1,fill="white",color="black")and then I want to fill the color of histogram by probable=1 and probable=0, could anyone help me in this? My data: structure(list(probable = c(1L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 1L,

I can't get my simultaneous equations to work using system fit. Please help. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) str(Empdata) Empdata$gnipc<-as.numeric(Empdata$gnipc) install.packages("systemfit") library("systemfit") pdata <- plm.data(Empdata,

Dear friends, I have a weekly time series which starts on Jan 4th, 2003 and ends on december 31st, 2016. I set up my ts object as follows: MyTseries <- ts(mydataset, start=2003, end=2016, frequency=52) MyModel <- auto.arima(MyTseries, d=1, D=1) MyModelForecast <- forecast (MyModel, h=12) Since my last observation was on december 31st, 2016 I expected my forecast date to start on

Hi, I'm trying to understand some details about an example maintened in [1]. According that link, I have total.data as a data set (am I right?). But I don't understand how is built that table. I saved the dataset in a file, with dput(), and had something like this: structure(list(df.all = structure(list(V1 = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,