similar to: Help needed with ks.test

Dear R-Users, is there any statement to fit a orthogonal regression in R environment? Many thanks in advance. Best regards, Vito Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the scientific learning process." George E. P. Box "Statistical thinking will one day be as necessary for efficient

Hi! I am searching for the Cochran-Armitage-trend-test. Is it included in an R-package? Thank you! --

When using fitdistr() with the exponential, log-normal and beta distributions, you get the relevent rate, mean, standard deviation, shape1 and shape2 but you get a number bellow those that are in () and I was wandering what exactly those numbers represent and how they relate to the data. Many thanks Mark Miller

Dear all, I'm looking for some material on data mining with R. I have something from Luis Torgo but I'd like to see something else. If anybody could help me I'll be thankful Adri??n

Hello, anyone got an idea on how to use stl() so that the remainder eventually becomes white noise? i used stl repeatedly but there is autocorrelation in the remainder that i can't get rid of. os: linux suse9.3 ------------------------------------------------ Sebastian Leuzinger Institute of Botany, University of Basel Sch??nbeinstr. 6 CH-4056 Basel ph 0041 (0) 61 2673511 fax 0041 (0)

hi all i have a another stats question. i would like to solve the following question: y(i)=a+b*x(i)+e(i) i.e. estimate a and b (they should be fixed) but i dont want to specify the standard density to the straight line. this can be done using kernel regression. the fitted line is however fitted locally. does anyone have a reference that will help me with my problem. i am still new to

Hi, my name is Giacomo. I would like to know how to create a Trend variable in a regression using R. Thank you for your help. My best regards, Giacomo --------------------------------- [[alternative HTML version deleted]]

Does p-value on Box.test(data,lag=l) returns probability, that H0: cor(1)=cor(2)=..=cor(l)=0 holds? Thanks. [[alternative HTML version deleted]]

Hello, I'm trying to calculate a chi-squared test to see if my data are different from the theoretical distribution or not: chisq.test(rbind(c(79, 52, 69, 71, 82, 87, 95, 74, 55, 78, 49, 60),c(80,80,80, 80, 80, 80, 80, 80, 80, 80, 80, 80))) Pearson's Chi-squared test data: rbind(c(79, 52, 69, 71, 82, 87, 95, 74, 55, 78, 49, 60), c(80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80,

hi, rgev function gives me random deviates and I have a data set which I am fitting to an EVD,IS there a way I can plot both observed and ideal evd on the same plot thankyou Rangesh

Hi there, I'm a newbie, plesae bear with me. I have a dataset with about 10000 ~ 30000 data points. Would like fit to both Gamma and Normal distribution to see which one fits better. How do I do this in R? Or I could do a normality test of the data, if it's normal, I then will do a normal fit, otherwise, a gamma fit. But again, I don't know how to do this either. Please help! David

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

Hi everybody, while performing ks.test for a standard exponential distribution on samples of dimension 2500, generated everytime as new, i had this strange behaviour: >data<-rexp(2500,0.4) >ks.test(data,"pexp",0.4) One-sample Kolmogorov-Smirnov test data: data D = 0.0147, p-value = 0.6549 alternative hypothesis: two.sided >data<-rexp(2500,0.4)

Hello everybody, i'm having some trouble performing correspondence analysis with R for Mac OS X. Does anyone know about some useful package? And also, if i had found coordinates of points representing row and column profiles, how do i put them in a single figure with labels identifying each one of them? This thing is getting me almost crazy... Thank you in advance for answering, bye

DeaR R-useRs, I'm trying to fit a logist model with these data: > dati y x 1 1 37 2 1 35 3 1 33 4 1 40 5 1 45 6 1 41 7 1 42 8 0 20 9 0 21 10 0 25 11 0 27 12 0 29 13 0 18 I use glm(), having this output: > g<-glm(y~x,family=binomial,data=dati) Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart =

Hi, I want to plot the residuals of a least-squares regression. plot(lm(y~x), which=1) does this, but it plots the y-axis of my data on the x-axis of the residuals plot. That is, it plots the residual for each y-value in the data. Can I instead use the x-axis of my data as the x-axis of the residuals plot, showing the residual for a given x? Thanks! Jason Priem University of North

Hi everybody, i'm dealing with some percentage tables, of which i should test rowwise if the entries are sgnificantly equal or not. Namely, on row 1, test H0: element 1= element2, H0: element 1= element3...H0: element 2= element3...H0: element n-1= element n. The same on the other rows. Anybody knows how this can be done in quick way? I don't have large matrices, but it seems quite

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

Hi, you can address to a single ts in a multivariate ts object by namets[,index]. See this example: > dati X Y 1 100 200 2 150 210 3 180 220 4 200 230 5 220 250 > serie<-ts(dati,start=1999) > serie Time Series: Start = 1999 End = 2003 Frequency = 1 X Y 1999 100 200 2000 150 210 2001 180 220 2002 200 230 2003 220 250 > serie[,1] ## first ts Time Series: Start =

Dear R-useRs, I've written a contribute (in Italian language) concering fitting distribution with R. I believe it could be usefull for someones. It's available on CRAN web-site: http://cran.r-project.org/doc/contrib/Ricci-distribuzioni.pdf Here's the abstract: This paper deals with distribution fitting using R environment for statistical computing. It treats briefly some