similar to: How do I get rid of list elements where the value is NULL before applying rbind?

I must have missed something simple, but still, i don't know what. I obtained my basic data as follows: x <- sprintf("SELECT m_id,sale_date,YEAR(sale_date) AS sale_year,WEEK(sale_date) AS sale_week,return_type,0.0001 + DATEDIFF(return_date,sale_date) AS elapsed_time FROM `merchants2`.`risk_input` WHERE DATEDIFF(return_date,sale_date) IS NOT NULL") moreinfo <- dbGetQuery(con,

I am feeling rather dumb right now. I created what I thought was a data.frame as follows: aaa <- lapply(split(moreinfo,list(moreinfo$m_id),drop = TRUE), fun_m_id) m_id_default_res <- do.call(rbind, aaa) print("==========================================") m_id_default_res print("==========================================") ndf <- m_id_default_res[, c('mid',

The data.frame is constructed by one of the following functions: funweek <- function(df) if (length(df$elapsed_time) > 5) { rv = fitdist(df$elapsed_time,"exp") rv$year = df$sale_year[1] rv$sample = df$sale_week[1] rv$granularity = "week" rv } funmonth <- function(df) if (length(df$elapsed_time) > 5) { rv =

>From the documentation I have found, it seems that one of the functions from package plyr, or a combination of functions like split and lapply would allow me to have a really short R script to analyze all my data (I have reduced it to a couple hundred thousand records with about half a dozen records. I get the same result from ddply and split/lapply: >

Hi r-helpers, When I issue the command latex(anova(raw1.lmer0, raw1.lmer, raw1.lmerI), file = 'raw1.tex', rownamesTexCmd = c('baR', 'addit', 'multip'), longtable = F, dcolumn = T, booktabs = T, t able.env = F, colheads = NULL, colnamesTexCmd = c ('', 'df', 'aic', 'bic', 'logl', 'chisq', 'chisqdf',

Hi, I' am doing a stats project using R to work out the size of a t-test and wilcoxon test depending on the distribution and sample size. I just can't get it to work - I want to put my results from the function size() into an array.At the moment I keep getting the error message:Error in res[distribution, test, samplesize] <- results : subscript out of boundsCan anyone tell me where

Hi, I'm trying to get better at things like lapply but it still stumps me. I have a function I've written, tested and debugged using individual calls to the function, ala: ResultList5 = DoAvgCalcs(IndexData, Lookback=5, SampleSize=TestSamples , Iterations=TestIterations ) ResultList8 = DoAvgCalcs(IndexData, Lookback=8, SampleSize=TestSamples , Iterations=TestIterations ) ResultList13

Hi Hugo, I've been able to replicate your bug, including for other distributions (runif, rexp, rgamma, etc) which shouldn't be surprising since they're probably all drawing from the same pseudo-random number generator. ?Interestingly, it does not seem to depend on the choice of seed, I am not sure why that is the case. I'll point out first of all that the R-devel mailing list is

Hi Hugo, I've been able to replicate your bug, including for other distributions (runif, rexp, rgamma, etc) which shouldn't be surprising since they're probably all drawing from the same pseudo-random number generator. ?Interestingly, it does not seem to depend on the choice of seed, I am not sure why that is the case. I'll point out first of all that the R-devel mailing list is

Dear colleague, I not sure this R code is correctly ? I would to show the number of Sample Size at Sample Size Axis that line draw from Power Axis (80%) from R code. How I show this and select the most appropriate of this power (.79955687 - 80983575). Thank for your help and answer. Best Regards, Nikom Thanomsieng, Email: nikom at kku.ac.th .... #Power analysis: Sample size for

Dear R helpers exposure <- data.frame(id = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20), ead = c(9483.686,50000,6843.4968,10509.37125,21297.8905,50000,706152.8354, 62670.5625, 687.801995,50641.4875,59227.125,43818.5778,52887.72534,601788.7937, 56813.14859,4012356.056,1419501.179,210853.4743,749961,6599.0862), pd =

I generate random vector from Weibull distribution sampWB <-urweibull(sampleSize, shape=shape.true, scale=scale.true, lb=0, ub=Inf) how can I create subvector containing 30% of samplesize of sampWB which should be assigned as Censored data? The probability for each value in sampWB can be uniform to be included in the subvector.

On 05/10/2018, 09:45, "R-help on behalf of hmh" <r-help-bounces at r-project.org on behalf of hugomh at gmx.fr> wrote: Hi, Thanks William for this fast answer, and sorry for sending the 1st mail to r-help instead to r-devel. I noticed that bug while I was simulating many small random walks using c(0,cumsum(rnorm(10))). Then the negative

Dear R users, I am trying to simulate some multitrait-multimethod models using the packages sem and psych but whatever I do to deal with models which do not converge I always get stuck and get error messages such as these: "Error in summary.sem(M1) : coefficient covariances cannot be computed" "Error in solve.default(res$hessian) : System ist f?r den Rechner singul?r: reziproke

Hi all, Since two days I am trying to find a solution to be able to create beanplots for my data. When I call the beanplot function the following error appears: > beanplot(y1 ~ x1, log="", what=c(1,1,1,0), ylim=c(0,1)) > Error in bw.SJ(x, method = "dpi") : sample is too sparse to find TD What is really strange: I have 32 different vectors and the problem occurs for

Hi I'm conducing a meta-analysis using the meta package. Here's a bit of code that works fine - tmp <- metacont(samplesize.2, pctdropout.2, sddropout.2, samplesize.1, pctdropout.1, sddropout.1, data=Dataset, sm="WMD") I would now like to control for a couple of variables (continuous and categorical) that aren't in the equation. Is meta

sampleSize <- 20 shape.true <- 1.82 scale.true <- 987 sampWB <- rweibull(sampleSize, shape=shape.true, scale=scale.true) print(sampWB) censidx <- sample(1:length(sampWB), length(sampWB)*0.3) Censored.data <- sampWB[censidx] noncensidx <- defines the rest values of the vector which is not included at Censored.data? [[alternative HTML version deleted]]

Hi, I write below code for simulation for weibull- estimating parameters by weibullMLE function, Although I define metrix for the variables still I got this message: number of items to replace is not a multiple of replacement length Any suggestion > est=matrix (NA, 2,2) > se=matrix (NA, 2,2) > for ( p in 1:2) { + sampleSize <- 20 + shape.true <- 1.82 + scale.true <- 987 +

Please forgive me, I feel exceptionally like a newbie. Although I've read screeds of documentation, I just can't see how this is done. I have a data frame that contains a number of pass/fails for certain variable sizes. From that, I would like to form another data frame that contains the proportions of pass/fails per variable. So, for example: df <- data.frame( Var=c(3,3,3,4,4),

My last query related to this referred to a problem with not being able to store data. A suggestion was made to try to convert the data returned by fitdist into a data.frame before using rbind. That failed, but provided the key to solving the problem (which was to create a data.frame using the variables fitdist produces in the object it returns). I now have almost everything working as