similar to: Conditional sampling

R users, I have been trying to write a program in R that will extract rows from a data frame and combine the rows into a new smaller data frame while meeting several criteria. I would greatly appreciate any advice that could help me get started down the right path. What I want to do is to extract two rows WEEK (26 weeks total) from the data frame by sampling without replacement from the

R users, I am trying to generate a randomized weekday survey schedule that ensures even coverage of weekdays in the sample, where the distribution of variable DOW is random with respect to WEEK. To accomplish this I need to randomly sample without replacement two weekdays per week for each of 27 weeks (only 5 are shown). However, I need to sample from a sequence (3:7) that needs to be

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,

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

Hello all, I am trying to sort rows of one matrix by rows of another. Given a1 and a2: ------ > a1 [,1] [,2] [,3] [1,] 7 6 8 [2,] 4 2 4 [3,] 4 7 2 [4,] 0 3 8 a1 <- structure(c(7, 4, 4, 0, 6, 2, 7, 3, 8, 4, 2, 8), .Dim = c(4L, 3L)) > a2 [,1] [,2] [,3] [1,] 101 102 103 [2,] 101 102 103 [3,] 101 102 103 [4,] 101 102 103 a2 <-

Hello, I want to use lme to fit two (or more) models, and then compare the fits on each individual. I know how to write my own code to do this (for each individual, plot the raw data, followed by lines() to plot each fitted curve) but I would like to use plot(augPred(... as it produces a nice trellis plot. I thought I could do this with par(new=T) but it does not seem to work.

what am I doing wrong? chron(as.character(f), format=c(dates="%m/%d/%y", times="%h:%m")) f <- structure(c(51L, 60L, 66L, 87L, 90L, 115L, 23L, 35L, 37L, 6L, 12L, 55L, 84L, 96L, 109L, 17L, 29L, 41L, 3L, 74L, 94L, 102L, 30L, 8L, 46L, 69L, 107L, 15L, 25L, 39L, 1L, 71L, 95L, 19L, 56L, 62L, 76L, 85L, 99L, 111L, 42L, 4L, 52L, 61L, 67L, 91L, 13L, 24L, 36L, 38L, 7L, 81L, 82L, 57L,

Hello everyone, My progress has stalled on finding a way of creating a somewhat complicated variable to add to my existing dataframe and I am hoping one of you could help me out. The dataframe below contains only a fraction of the data of my complete dataframe, but all of the variables. What I want to do is add another variable named 'WEEK' to this dataframe that is assigned 1 for row 1

Hi R-Help, data at bottom I've been struggling with a problem where I need to order based on 1) the Frequency "Freq" and 2) keeping each group of 3 of the same type together "Var2" but I want across all groups it to go "high to low" based on the earn factor. Thank you! structure(list(Var1 = structure(c(1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 2L, 3L, 1L,

Hi all: I am trying to use the ddply function to estimate the mean of 'Total','Fry','Smolt' and 'Fry.Eq' columns without success. I have the dput of my dataset below. I wonder if someone can give me a hand with this function. # dput(winter) winter <-structure(list(IDDate = structure(c(37L, 48L, 59L, 62L, 63L, 64L, 65L, 66L, 67L, 38L, 39L, 40L, 41L, 42L, 43L,

Hi, Try this: #mat1 is the data res<-do.call(cbind,lapply(seq_len(nrow(mat1)),function(i) {new1<-do.call(rbind,lapply(seq_len(nrow(mat1[-i,])),function(j) {x1<-rbind(mat1[i,],mat1[j,]); x2<-(abs(x1[1,1]-x1[2,1])*abs(x1[1,5]-x1[2,5]))+(abs(x1[1,2]-x1[2,2])*abs(x1[1,6]-x1[2,6]))+(abs(x1[1,3]-x1[2,3])*abs(x1[1,7]-x1[2,7]))+(abs(x1[1,4]-x1[2,4])*abs(x1[1,8]-x1[2,8]))}));new1}))

Hi all, I would like to ask you for help. I did a dotplot - using dotchart function. There are two localites (loc) with values 75 or 56 in my data ZZ. The f column has 4 levels: P1, S1, S8, R6. The dataframe is ordered by N value, pchloc value is assign to use "pch" in plot. > head(ZZ) loc f N color ordered pchloc 98 75 S1 6.39 green 1 16 99 75 S8 6.44 blue

I am having difficulty understanding how I would constrain a data set by filtering out 'records' based on certain criteria. Using SQL I could query using 'select * from my.data where LithClass in ('sand', 'clay')' or some such. Using subset, there seem to be ghosts left behind (that is, all of the LithClass *.Labels* remain after subset) > dput(tcc)

Hi All, I have a scatter plot produced using ggplot2 and I want to add the regression line to this scatter plot. I suppose I can use geom_smooth() to do this, but for the sake of learning ( I am new both to R and ggplot2), I want to try and add it as a function (something that curve() does in the standard R plotting). I did some search and found that stat_function() can be used for this. But

Hi there, I am having a little problem with combining three scale_manual commands in a facet plot. I am not able to combine the three different characteristics, instead ending up with three different descriptions next to the graph for the same geom. I would like to see two separate labels (not three); one describing lines 1-7 and the other 8-14. For each of the treatments (A-B) I want a

R experts, How could I extract the week number from a date vector (in Date class) such that week numbering (week 1...2...) begins (May 01) and ends (October 31) on the same specific dates each year? Week numbering must conform to the following day numbering format (Sat=1,Sun=2,Mon=3.....Fri=7). This means that new weeks must begin on Saturdays, and end on Fridays (except for the first date

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

> On Dec 6, 2017, at 5:07 AM, Paul Bernal <paulbernal07 at gmail.com> wrote: > > 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)

Thank you very much David. As a matter of fact, I solved it by doing the following: MyTimeSeriesObj <- ts(MyData, freq=365.25/7, start=decimal_date(mdy("01-04-2003"))) After doing that adjustment, my forecasts dates started from 2017 on. Cheers, Paul 2017-12-06 12:03 GMT-05:00 David Winsemius <dwinsemius at comcast.net>: > > > On Dec 6, 2017, at 5:07 AM, Paul