similar to: exercise in frustration: applying a function to subsamples

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 =

Here is the function that makes the data.frames in the list: funweek <- function(df) if (length(df$elapsed_time) > 5) { res = fitdist(df$elapsed_time,"exp") year = df$sale_year[1] sample = df$sale_week[1] mid = df$m_id[1] estimate = res$estimate sd = res$sd samplesize = res$n loglik = res$loglik aic = res$aic bic = res$bic chisq =

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,

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

I have a simple query as follows: "SELECT m_id,sale_date,YEAR(sale_date),WEEK(sale_date),return_type,DATEDIFF(return_date,sale_date) AS elapsed_time FROM risk_input" I can get, and view, all the data that that query returns. The question is, sale_date is a timestamp, and I need to call split to group this data by m_id and the week in which the sale occurred. Obviously, I would

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',

Hi listers, I am having some trouble in a matrix multiplication... I have already checked some posts, but I didn't find my problem... I have the following code... But I am not getting the right multiplication... I checked the dimension and they are fine... id_y <- array(1:10,dim=c(2,1,5)) id_yt<-aperm(id_y,c(2,1,3)) m_id<-array(dim=c(dim(id_y)[1],dim(id_y)[1],dim(id_y)[3])) for (i in

Factor out copying the overlays to final disk images into a separate function. Signed-off-by: Roman Kagan <rkagan@virtuozzo.com> --- v2v/v2v.ml | 227 +++++++++++++++++++++++++++++++------------------------------ 1 file changed, 114 insertions(+), 113 deletions(-) diff --git a/v2v/v2v.ml b/v2v/v2v.ml index afffde2..703038c 100644 --- a/v2v/v2v.ml +++ b/v2v/v2v.ml @@ -110,121 +110,9 @@ let

Dear Sirs, The below listed code fits a gamma and a pareto distribution to a data set danishuni. However the distributions are not appropriate to fit both tails of the data set hence a mixed distribution is required which has ben defined as "mixgampar" as shown below. library(fitdistrplus) x<- danishuni$Loss fgam<- fitdist(x,"gamma",lower=0) fpar<-

All, I'm in the process of upgrading an LLVM client from using 3.8 to using 4.0 and am running into the following issue: // compile with: // clang++ -std=c++11 -Wno-c++14-extensions -S -emit-llvm // ~/chrono.cpp -o chrono.ll #include <chrono> #include <ratio> #include <thread> using namespace std; using namespace std::chrono; using tick = ratio<1, 300>; using

Hi, Well, i need some help, practical and theoretical. I am wondering why the fitdistplus (mle function) is returning an error for this code: [code] x1 <- c(100,200,140,98,97,56,42,10,2,2,1,4,3,2,12,3,1,1,1,1,0,0); plotdist(x1); descdist(x1, boot =1000); y<- sum(x1); d= as.vector(length(x1)); for(i in 1:length(x1)){ d[i] = x1[i]/y; } fitdist(d, "beta") [/code] Error:

Hi, I am trying to estiamte parameters for gamma distribution using mle for below data using fitdist & fitdistr functions which are from "fitdistrplus" & "MASS"packages . I am getting errors for both functions. Can someone please let me know how to overcome this issue?? data y1<- c(256656, 76376, 6467673, 46446, 3400, 3100, 5760, 4562, 8000, 512, 4545, 4562,

Hi all, I'm currently working on the fitdistrplus package (that basically fit distributions). There is something I do not understand about the generic function summary. In the current version on CRAN, there is no NAMESPACE saying S3method(summary, fitdist) . However if we use summary on an object send by fitdist function it works fine... According to R-lang, we have " The most

Capture the results of the apply command into an object and then work with that. Here is one way to do it: > res <- apply(C, 2, fitdist, "gamma") > out <- c( res$A$estimate["shape"], res$B$estimate["shape"], res$A$estimate["rate"], res$B$estimate["rate"]) > names(out) <- c("A shape","B shape","A

Hi, I am trying to fit a Johnson SB distribution using fitdist function in fitdistrplus Library. I have defined the Johnson SB distribution from ( http://www.ntrand.com/johnson-sb-distribution/) . But it gives me the follwing errors. Any help would be appreciated #xi = xi #lambda =l #delta =d #gamma = g djohn = function(x,xi,l,d,g) (d/(l*sqrt(2*pi)*((x-xi)/l)*(1-((x-xi)/l))))*exp[-0.5*(g +

Hi, I am trying fit certain data into Beta distribution. I get the error saying "Error in fitdist(discrete_random_variable_c, "beta", start = NULL, fix.arg = NULL) : the function mle failed to estimate the parameters, with the error code 100" Below is the sorted data that I am trying to fit. Where am I going wrong. Thanks a lot for any help. Vinod

One of the recurring themes in the recent UserR conference was that many people find it difficult to find the functions they need for a particular task. Sandy Weisberg suggested a small idea he would like to see: a hints function that given an object, lists likely operations. I've done my best to implement this function using the tools currently available in R, and my code is included at the

One of the recurring themes in the recent UserR conference was that many people find it difficult to find the functions they need for a particular task. Sandy Weisberg suggested a small idea he would like to see: a hints function that given an object, lists likely operations. I've done my best to implement this function using the tools currently available in R, and my code is included at the

Hi, Let say I have data by two columns A and B, and I have fit each column using the gamma distribution by 'fitdist' . I just want the result show only the shape and rate only. Eg: library(fitdistrplus) A <-c(1,2,3,4,5) B<-c(6,7,8,9,10) C <-cbind(A,B) apply(C, 2, fitdist, "gamma") Output show like this: $A Fitting of the distribution ' gamma ' by maximum

Does anyone know how to get CID working in AEL2 ? In extensions.conf you can do: exten => 111/666,1,PlayBack(demo-congrats) exten => 111/666,2,Hangup() exten => 111,1,PlayBack(demo-moreinfo) exten => 111,2,Hangup() and if callerid 666 dialed 111, they would get demo-congrats, everyone else gets demo-moreinfo. In AEL: 111 => { Playback(demo-moreinfo);