similar to: fitting a distribution to a ecdf plot

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 there, Does R has built-in codes for nonpara. bivariate regression so that I can estimate the joint distribution of two variables as a function of some covariates? Thanks a lot. --------------------------------------------------- Ximing Wu Department of Economics University of Guelph Guelph, Ontario, Canada, N1G 2W1 Tel: (519) 842-4120, ext 53014 Fax: (519) 763-8497 email: xiwu at

Hello everyone, I was trying to do some distribution fitting with a numerical field called Tolls. The sample size = 999 rows. Basically I assigned the Toll data to a new variable K by doing: k<-dtest$Toll After that, tried to fit a gamma distribution by doing: fitG<-fitdist(k, "gamma") Then the following messages showed (oh and I checked for empty rows before doing this):

>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 lovers Here is a numerical vector test > test [1] 206 53 124 112 92 77 118 75 48 176 90 74 107 126 99 84 114 147 99 114 99 84 99 99 99 99 99 104 1 159 100 53 [33] 132 82 85 106 136 99 110 82 99 99 89 107 99 68 130 99 99 110 99 95 153 93 136 51 103 95 99 72 99 50 110 37 [65] 102 104 92 90 94 99 76 81 109 91 98 96 104 104 93 99 125 89

Dear all, I am ploting two boxplot of two chemical variables using the format boxplot(Alkalinity, logAlkalinity, log="y", col=c("lightblue"), lwd=0.6, boxwex=0.3) However when I plot like this, the distance between the two boxplots is very big and as well the distance of each boxplot from the plot area, left and right. How can I minimise that distance between the boxplots and

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

On Wed, Nov 29, 2017 at 6:30 AM, Gene Cumm <gene.cumm at gmail.com> wrote: > On Tue, Nov 28, 2017 at 2:38 PM, Joakim Tjernlund > <Joakim.Tjernlund at infinera.com> wrote: >> On Mon, 2017-11-27 at 18:18 -0500, Gene Cumm wrote: > >>> On Mon, Nov 27, 2017 at 6:07 PM, Joakim Tjernlund >>> <Joakim.Tjernlund at infinera.com> wrote: >>> > On

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

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<-

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

Dear all, I want to do some time plots and actually the dates are in the format of dd/mm/yyyy. So first I input my dataframe in R in a csv form. What I do is DF<-read.csv("C:/Documents and Settings/DF.csv") DATE<-as.Date(DATE, "%d/%m/%Y") # to tell R that DATE column is indeed dates with(DF, plot(DATE,pH)) Until here it works fine, but I have the graph plotting

Hi, sorry for repeating the question but this is kind of important to me and i don't know whom should i ask. So as noted before when I do a parameter fit to the beta distr i get: fitdist(vectNorm,"beta"); Fitting of the distribution ' beta ' by maximum likelihood Parameters: estimate Std. Error shape1 2.148779 0.1458042 shape2 810.067515 61.8608126 Warning

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

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 +

Dear all,? I am really sorry for this. I have attached the script and a .csv file with an example.? Hope this will help. Many thanks,Maria ???? 11:53 ?.?. ???????, 20 ????????? 2017, ?/? Duncan Murdoch <murdoch.duncan at gmail.com> ??????: On 20/11/2017 6:38 AM, Maria Lathouri via R-help wrote: >? Dear all > I know that it is a very simple question but it seems that I cannot

Dear all, I am trying to make boxplots in one diagram but it is not working. Actually I have a large dataset, around 35 water quality variables with different units and of course in different ranges (some are orders of magnitude bigger than others). I want to produce one diagram with all the boxplots of the variables of my dataset. I tried these series of commands: >oldpar <-

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 =

Dear all, I would like to use the following function fitdist(data, distr, method=c("mle", "mme", "qme", "mge"), start=NULL, fix.arg=NULL, ...) for many different distr values like distr=c("norm","lnorm","pois") (just a small example) and take back into a list the parameter name which is what is inside distr plus what the