search for: goodfit

Hello, I am a student and for project I need R. I have one problem regarding function goodfit(). Does goodfit() require frequency count of numbers or numbers themselves? For example suppose I have data say 150 readings.Do I need to use goodfit() directly on data or should I make suitable no of bins and then apply goodfit()? Aswad [[alternative HTML version deleted]]

I have troubles understanding how goodfit() function in the vcd package computes the Pearson coefficient. Can anybody provide more information on the computation? In particular, for HorseKicks data in vcd package, goodfit() yields > oo <- goodfit(HorseKicks,type="poisson",method="MinChisq") > summary(oo)...

...o. What I need to know is how to obtain the application itself. My thanks in advance for any help you can provide. MS ------- Forwarded message follows ------- Date sent: Tue, 23 Sep 2003 09:14:28 -0400 From: Michael Friendly <friendly at yorku.ca> Subject: Re: goodfit macro To: shott at csbs.csbs.uni.edu Send reply to: friendly at yorku.ca Organization: York University You can also carry out goodness of fit tests using the function goodfit in the vcd package for R (a free version of S/Splus), http://www.r-project.org -Michael Michael Shott...

...method to "ML" and try again. I tried the run the first example from the documentation and it failed with the same error. Changing the estimation method to ML worked. @List: Can anyone else verify the error I got? I literally ran the following two lines interactively from the example for goodfit: dummy <- rnbinom(200, size = 1.5, prob = 0.8) gf <- goodfit(dummy, type = "nbinomial", method = "MinChisq") and got back Warning messages: 1: In pnbinom(q, size, prob, lower.tail, log.p) : NaNs produced 2: In pnbinom(q, size, prob, lower.tail, log.p) : NaNs produced A...

Dear All, I run the goodness of fit test using goodfit() in vcd package. The result is as follow: Goodness-of-fit test for poisson distribution X^2 df P(> X^2) Pearson 1.053348 2 0.5905661 Warning message: In summary.goodfit(gf) : Chi-squared approximation may be incorrect I want to save the the test statistics(X^2), df, a...

Hey, Does anyone know if there is a way to get back from goodfit what it estimated the parameters to be? I used the code fit<-goodfit(round(data$PLX_NRX),type="nbinomial" and got a pretty good fit. I could not however duplicate this good fit with any parameter estimates that I had. Any ideas??? Thanks, Elizabeth Lawson -------------...

Hello, Sample code: library("vcd") dummy <- rnbinom(200, size=1.5, prob=0.8) gf <- goodfit(dummy, type="nbinomial", method="MinChisq") plot(gf) I would like to: 1. add a lgened stating the bars show the actual counts and the red dots - the fit. 2. show the goodness-of-fit values calculated somewhere on an empty white space ob the plot. But... the legend command does...

...[1:5] "A" "B" "C" "D" ... I also tried: vex <- c(109,65,22,3,1) vec <- as.table(vex) str(vec) table [1:5(1d)] 109 65 22 3 1 - attr(*, "dimnames")=List of 1 ..$ : chr [1:5] "A" "B" "C" "D" ... goodfit(HorseKicks) works fine goodfit(vec) does not Thank you, Thomas This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, co...

...nt to test if my data are poisson in distribution or normal. My first question is whether it is more appropriate to model my data according to a poisson distribution (if my test says it conforms) or use transformed data to normalise the data distribution? I have been using the vcd package gf<-goodfit(Y,type= "poisson",method= "MinChisq") but i get the following error message Warning message: In optimize(chi2, range(count)) : NA/Inf replaced by maximum positive value I then binned my count data to see if that might help V1 V2 1 5 34 2 10 30 3 15 10 4 20 8 5 25...

Dear all, I am analyzing counts of seabirds made from line transects at sea. I have been fitting Poisson and negative binomial distributions to the data using the goodfit function from the vcd library. I would also like to evaluate how well a quasi-poisson distribution fits the data. However, none of the potentially suitable functions I have identified (goodfit(vcd), fitdistr(MASS), fit.dist(gnlm)) includes the quasipoisson distribution as one of their standard name...

[code]library(MASS) x=c(rep(0,8096), rep(1,1629), rep(2,233), rep(3,38), rep(4,4) ) x.bar=round(mean(x),4) x.var=round(var(x),4) p.hat=round(x.bar/x.var,4) alpha.hat=round(x.bar*p.hat/(1-p.hat),4) fitdistr(x, "Negative Binomial") fitdistr(x, "Poisson")[/code] 1- fitdistr(x, "Negative Binomial") the parameters got here,

...tribution 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 goodfit in package vcd, which seems to it for some discrete distributions. Thank you for help, Christian *********************************************************************** Christian Hennig Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg hennig at math.uni-hamburg.de, http://www.math.uni-hamb...

...d AICctab in the bbmle package to compare model IC.  However, I need to test for the goodness of fit of the full model, and have not been able to find a Pearson's Chi Squared statistic in any of the output.  Am I missing it somewhere?  Is there a way to run the test using either chisq.test() or goodfit()?  I would appreciate any suggestions on how to test for goodness of fit in negative binomial models.   Thanks,   Tim Clark Dept. of Zoology University of Hawaii [[alternative HTML version deleted]]

...ried samples but I have some problems to obtain results for a logistic regression under R. The following SPSS script LOGISTIC REGRESSION vir /METHOD = FSTEP(LR) d007 d008 d009 d010 d011 d012 d013 d014 d015 d016 d017 d018 d069 d072 d073 /SAVE = PRED COOK SRESID /CLASSPLOT /PRINT = GOODFIT CI(95) /CRITERIA = PIN(.10) POUT(.10) ITERATE(40) CUT(.5) . predicts vir (value 0 or 1) according to my parameters d007 to d073. It gives me the parameters to retain in the logistic equation and the intercept. The calculation is made from a set of values of about 1.000 cases. I have been unab...

...10. Re: Using 'sapply' and 'by' in one function (hadley wickham) 11. Error in optim while using fitdistr() function (Jason Q. McClintic) 12. Re: Using 'sapply' and 'by' in one function (Gabor Grothendieck) 13. Re: Error while using fitdistr() function or goodfit() function (Jason Q. McClintic) 14. Re: Error while using fitdistr() function or goodfit() function (Aswad Gurjar) 15. Re: Using 'sapply' and 'by' in one function (hadley wickham) 16. building packages for Linux vs. Windows (Erin Hodgess) 17. Re: building packag...

I have a dataset which I want to model using a Poisson distribution, with a given parameter. I would like to know what is the proper way to do a ''goodness of fit'' test using R. I know the steps I''d take if I were to do it ''manually'': grouping the numbers into classes, calculating the expected frequencies using ''ppois'', then

Hi, this is probably a very newbie statistical question. I have some experimental data. My hypothesis is that the data are binomially distributed with a known N and p. I am trying to obtain a sort of p-value to tell me whether or not my hypothesis is correct. What can I do with R? Thank you, Pier Luca

Good morning, in my work I need to study data distributions and so I need to fit the experimental distribution by theoretical curves such as normal, Poison, binomial and so on. I'd like to know, given a vector of data, for example x<-rnorm (1000, 10) if they follow a normal distribution. I'd like to do a fit (to estimate the parameters of the theoretical distribution) and then a

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

I haven't been an R lister for a bit, but I hope to enlist someone's help here. I think this is a simple question, so I hope the answer is not much trouble. Can you please respond directly to this email address in addition to the list (if responding to the list is warranted)? I have a histogram and I want to see if the data fit a Poisson distribution. How do I do this? It is