similar to: Fw: random sampling steps in R with replacement

Dear all, Could someone assist me in random sampling steps/code in R? I have a main sample of 42 males and 165 females and I want to come up with about 1000 samples of 20 males and 20 females from this main sample. While at it, i would also like to come up Accuracy Ratios (ARs) with corresponding confidence intervals. Please assist. Thanks so much, Taby [[alternative HTML version

Hi all, I am having this error while trying to merge about 2 dataframes m_merge = merge(m_accts,m_op, by.y="CUST_ID",by.x="FORACID",all.y=TRUE,all.x=TRUE) Error: cannot allocate vector of size 10.0 Mb Taby [[alternative HTML version deleted]]

Hi all, Out of curiosity I googled my name yesterday to just see what new information  in the web there is associated with me. To  my surprise, I found in addition to the  questions i have posted on this forum, my email address and my signature details (name, address, telephone number) seem to appear everytime i pose a question. How can i conceal my personal details from the access of anyone when

Hallo, I modified a code given by Andrija, a contributor in the list  to achieve two objectives: create 1000 samples from a list of 207 samples with each of the samples cointaining 20 good and 20 bad. THis i have achievedcalcuate AUC each of the 1000 samples, this i get an error. Please see the code below and assist me. > data<-data.frame(id=1:(165+42),main_samp$SCORE,

Dear R-users, I need some  assistance. I am running some interactive variables for categorical variables. I have dgen(2 levels converted to dummy variables)  and dtoe(4-levels also converted to  dummy variables). So I have worked with them in two ways: i created a variable X1 = dgen*dtoe  and I get an error "Error in dgen * dtoe : non-conformable arrays"then i run a glm, binomial

Dear all, i have a dataset of about 400 records , with a variable that has  two levels 40 bad and 360 good among other variables,how do i come up  with10 random samples that have the composition of as the main sample  but maintaining the 40 bad 360 good with replacement, i recently discovered that my random samples generated dont maintain the ratio. My code is as  : mysample <-

I am currently trying to transpose some large panel data set ie transposing multiple rows in into a single column. instead the transpose functionality transposes all rows into columns. my sample data set looks like below: ACCT_NUM ACCOUNT_NAME TRAN_AMT DATE EMPLOYER 101913 GK 7489 30-Apr-10 PENSION 101913 GK 7489 30-May-10 PENSION 101913

Dear r user, please find my attached sample of the dataset i? am using to create a crosstable and eventually plot a histogram from the output. I am using? the cut2 function to create bins, about 7 of them using the code after reading the data: cluster <- cut2(cross_val$value, g=7) I get the warning: Warning message: In min(xx[xx > upper]) : no non-missing arguments to min; returning Inf

Hi all, Please help, I am getting an error when I try installing rattle. Error in as.GType(type) : Cannot convert RGtkBuilder to GType I have already installed gtk-2.12.9-win32-2  and gtk2-runtime-2.22.0-2010-10-21-ash and restarted R as instructions require. Please assist me Taby [[alternative HTML version deleted]]

Dear all,This is both an R and a statistics question. I want to test whether males and females of a given species tend to co-occur in a given sampling unit more frequently than expected by chance. I'm thinking about using a binomial distribution with p as the sex ratio of the entire population. So, even though the population sex ratio is close to 50:50, each sampling unit would have

Dear R users aim Barplot of insect trap catches (y variable trapcatch) at one specific station (variable FiBL_Hecke) from week 1-52 ( x variable week). It works well using the function tapply (sum trapcatch per week, males and females not separated), however, I intend to separate the y variable trapcatch in males and females (variable m_w: m and w) problem I used the function "add" to

Hi, I'm trying to work through a Nested ANOVA for the following scenario: 20 males were used to fertilize eggs of 4 females per male, so that female is nested within male (80 females used total). Spine length was measured on 11 offspring per family, resulting in 880 measurements on 80 families. I used the following two commands: summary(aov(Spinelength ~ Male*Female)) and

Hello All, I would like to report the following bug or maybe you can explain if I am wrong. I am sampling from two different populations with weights. The two populations have the same age groups and I want to distinguish where I am sampling from. That is why I am using a matrix such as: matrix age.group Male Females Weight.Males Weight.Females 1 1.1

Hi. I'm analysing some fish biological traits with a gam in mgcv. After several tries, I got this model log(tle) = sexcolor + s(doy, bs = "cc", by = sexcolor) +log(tl) sexcolor is a factor with 4 levels doy is "day of year", which is modeled as a smoother tl is "total length of the fish" The summary of this models is (only parametric coefficientes): Parametric

Greetings. I'm trying to recreate in R some regression models I've done in SAS, but I'm not getting the same results. My advisor suspects this may be due to differences in precision between R and SAS. Does anyone know where I can find specifications for R's type double? (It doesn't seem to be in the R Language Definition.) Thanks in advance for any help anyone can

this is the problem: load this R data frame over the internet and save it to your hard drive. http://rss.acs.unt.edu/Rdoc/library/twang/data/raceproling.RData please show how to save a dataset of males only (the variable male=1) to a new dataframe. Then do the same thing for females (male=0). Then show how to recombine the two datasets to belike the original one except that the female

I'm not sure how to best explain what I am after but here goes. I have a data frame with 2 geographical factors. One is the major region the other is the component regions. I am trying to process all the regions at the same time without using "for". So I need (think, I do) a list of matrices each structured according to the number of subregions within each region. So is there a

Dear friends, I have asked last few days about cross-random effects using PQL, but I have not receive any answer because might my question was not clear. My question was about analysing the salamander mating data using PQL. This data contain cross-random effects for (male) and for (female). By opining MASS and lme library. I wrote this code sala.glmm <- glmmPQL(fixed=y~WSf*WSM,

Hello to all R users, I use R for a year now and am dealing with geometric morphometrics of deer skulls. Yes, I am a biologist and my math skills are just beginning to brush up. To cut to the chase... I have two groups in my data (males and females) and my data is in a simple vector form. Now I need a bootstrap test for this value szc1 <- ((mean(maleCent)-mean(femaCent))^

Dear R Users, I am having trouble with lmer. I am looking at recombinant versus non recombinant individuals. In the response variable recombinant individuals are coded as 1's and non-recombinant as 0's. I built a model with 2 fixed factors and 1 random effect. Sex (males/females) is the first fixed effect and sexual genotype (XY, YY, WX and WY) the second one. Sexual Genotype is