similar to: goodness of fit between two samples of size N (discrete variable)

I simulate a uniform data and then transformed into Burr(1,3,1) data, which is of pdf: f(x)=[3*(x^2)] / [(1+x^3)^2], x>0 How can I perform a goodness-of-fit test (k-s, anderson-darling,chisq,cramer-von mises,...) on it (should highly accept) to get test-statistics & p-values? Thanks! Sincerely, Shelton Jin -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

Hi, I'm using the power.law.fit function from the igraph package to fit a power law distribution to some data. This function returns the power law exponent as it's only result. I would like to have some sort of goodness-of-fit and/or error estimate of the exponent returned. This paper: http://www.edpsciences.org/articles/epjb/pdf/2004/18/b04111.pdf suggests using the

Forum, I'm a grad student in Civil Eng, took some Stats classes that required students learn R, and I have since taken to R and use it for as much as I can. Back in my lab/office, many of my fellow grad students still use proprietary software at the behest of advisers who are familiar with the recommended software (Statistica, @Risk (Excel Add-on), etc). I have spent a lot of time learning

Dear All, Is there any modules to compute the chi-square goodness of fit , K.S. statistics and Anderson Darling nonparametric test and compre the fitting of a class of distributions using these tests? Thank you. Osama Hussien -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

Hi, Interpretation problem ! so what i did is by using the: >fit1 <- fitdist(vectNorm,"beta") Warning messages: 1: In dbeta(x, shape1, shape2, log) : NaNs produced 2: In dbeta(x, shape1, shape2, log) : NaNs produced 3: In dbeta(x, shape1, shape2, log) : NaNs produced 4: In dbeta(x, shape1, shape2, log) : NaNs produced 5: In dbeta(x, shape1, shape2, log) : NaNs produced 6: In

Hola, LLevo buscando desde hace tiempo como hacer el Goodness of fit test en R. Es decir, me explico, intento hacer una cosa parecida que se hace en Minitab, por ejemplo, yo tengo un conjunto de datos, y lo que quiero es sabes que tipo de distibución es, en minitab se hace un histograma para ver si se ajusta bien o no a la campana de Gauss, luego vemos si aproximar la distribución de la muestra

hello! i don't want to test my sample data for normality, but exponential- lognormal- or gammadistribution. as i've learnt the anderson-darling-test in R is only for normality and i am not supposed to use the kolmogorov-smirnov test of R for parameter estimates from sample data, is that true? can you help me, how to do this anyway! thank you very much! nadja

Hello, While doing test of normality under R and SAS, in order to prove the efficiency of R to my company, I notice that Anderson Darling, Cramer Van Mises and Shapiro-Wilk tests results are quite the same under the two environnements, but the Kolmogorov-smirnov p-value really is different. Here is what I do: > ks.test(w,pnorm,mean(w),sd(w)) One-sample Kolmogorov-Smirnov test data: w D

Dear R helpers, I have a bimodal dataset dealing with loss amounts. I have divided this dataset into two with the bounds for the first dataset i.e. dataset-A being 5,000$ to 100,000$ and the dataset-B deals with the losses exceeding 100,000$ i.e. dataset-B is left truncated. I need to fit truncated normal disribution to dataset - I having lower bound of 5000 and upper bound of 100,000. While I

Hi, I have the binned data (observed and generated from model)  that I would like to test using the anderson-darling goodness of fit test.  But I'm not sure which package in R to use. I tried ad.test(...) but it does not recognise the test by Vito Ricci in FITTING DISTRIBUTIONS WITH R   > ad.test(hist_hume_beec[,1],hist_hume_beec[,2]) Error: could not find function "ad.test"

Hi, I was wondering whether there is an implementation of the Kolmogorov-Smirnov goodness of fit test for discrete, ordinal scale data in R - I've only managed to find the test for continuous data. Thanks! Gila

According to https://icecast.org/docs/icecast-2.4.1/config-file.html: ssl If et to 1 will enable HTTPS on this listen-socket. Icecast must have been compiled against openSSL to be able to do so. Does the standard Icecast ditribution include SSL support, or must it be built manually to include this? I've read articles saying both are true. Which is correct?

Hello folks: I have a data frame which includes two numeric vectors: "Pa1" and "Ingr" (which represents income).  I run the following code on the R console: ingreso <- factor(ifelse(Ingr<=3000,"bajo","alto")) tapply(Pa1,ingreso,summary) boxplot(Pa1~ingreso) and it works fine.  However, when I "Sweave" through an rnw file containing that

Hi, is there any method for goodness of fit testing of an (as general as possible) univariate distribution with parameters estimated, for normal, exponential, gamma distributions, say (e.g. the corrected p-values for the Kolmogorov-Smirnov or Chi-squared with corresponding ML estimation method)? It seems that neither ks.test nor chisq.test handle estimated parameters. I am aware of function

I'm looking for goodness of fit tests for gamma distributions with large data sizes. I have a matrix with around 10,000 data values in it and i have fitted a gamma distribution over a histogram of the data. The problem is testing how well that distribution fits. Chi-squared seems to be used more for discrete distributions and kolmogorov-smirnov seems that large sample sizes make it had to

Thanking John for his suggestion I build this function which get the mode of both categorial and discrete data. Mode<-function(x){t<-table(x) if (is.numeric(x)) as.numeric(names(t)[t == max(t)]) else (names(t)[t == max(t)]) } Any other improvement and suggestion will welcome. Best Vito > s [1] 1 1 6 1 1 7 6 5 6 2 1 4 5 6 6 7 3 5 4 1 7 3 7 3 3 7 7 2 1 4 4 2 7 7 6 6 1 2 [39] 5 1 7 7

Hello all, Would somebody be kind enough to show me how to do a KS test in R for a lognormal distribution with ESTIMATED parameters. The R function ks.test()says "the parameters specified must be prespecified and not estimated from the data" Is there a way to correct this when one uses estimated data? Regards, Kwabena. -------------------------------------------- Kwabena Adusei-Poku

Dear R-Users, How can I use chisq.test() as a goodness of fit test? Reading man-page I?ve some doubts that kind of test is available with this statement. Am I wrong? X2=sum((O-E)^2)/E) O=empirical frequencies E=expected freq. calculated with the model (such as normal distribution) See: http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm for X2 used as a goodness of fit test. Any

Dear useRs, There is a new version 0.1-2 of the package surv2sample available on CRAN. Users of the previous versions should update because a bug in the function cif2.ks has been fixed. General information about the package: surv2sample provides various two-sample tests for right-censored survival data. Three main areas and corresponding methods are: * comparison of two survival

Dear useRs, There is a new version 0.1-2 of the package surv2sample available on CRAN. Users of the previous versions should update because a bug in the function cif2.ks has been fixed. General information about the package: surv2sample provides various two-sample tests for right-censored survival data. Three main areas and corresponding methods are: * comparison of two survival