similar to: Siegel-Tukey Test

Hi everybody! Is there any way to read a postscrit file into R? All the best to you Ralf Finne SYH University of Applied Sciences Vasa Finland

Hi experts! Have anybody experience in including an R-program as part of a larger system? In Matlab there is a toolbox that converts a m-script into C-code. One application in mind is that I do the model building in R, for estimating the risk for cancer based on clinical measurements. When the model is ready, a small R-program can simulate the model to estimate the risk for a new patient. The

Hi R-users Is there any functions in R that can implement "expert systems"? The aim of an expert system is to produce a probable diagnosis for a patient with certain symptoms. In the classical expert system a mumber of "experts" are asked to make "statements" on the probabilities for different diseases when a combination of systems would appear. One typical

Hi, I recently ran into the problem that I needed a Siegel-Tukey test for equal variability based on ranks. Maybe there is a package that has it implemented, but I could not find it. So I programmed an R function to do it. The Siegel-Tukey test requires to recode the ranks so that they express variability rather than ascending order. This is essentially what the code further below does. After the

Hello R friends, I am looking for a function to perform the Siegel-Tukey test in R. Can anyvbody help me? Thanks so much! J. Hedderich -- --------------------------------------------------------------- Dipl. Inform. J. Hedderich Institut f??r Medizinische Informatik und Statistik im Klinikum S.H. - Campus Kiel - Phone : 0431/5973182 Brunswiker Str.

Hi R-colleagues. In the sem-package i have a problem to introduce hidden variables. As a simple example I take an ordinary factor analysis. The program: cmat=c(0.14855886, 0.05774635, 0.08003300, 0.04900990, 0.05774635, 0.18042029, 0.11213013, 0.03752475, 0.08003300, 0.11213013, 0.24646337, 0.03609901, 0.04900990, 0.03752475, 0.03609901, 0.31702970)

I am Julia Cains from Brisbane. This is my first mail to this group and I have recently started learning the R language.   I am trying to learn the smoothening of the yield curve. However, I came across the CRAN package – “YieldCurve” meant for Modelling and estimation of the yield curve. The problem is I am not able to understand whether this package will help me to carry out smoothening of the

Hola a todos: En la estimación de parametros de Nelson-Siegel vienen definidos 3 argumentos: rate, maturity y MidTau. Este último lo define como un vector el cual indica el término medio del vencimiento para maximizar el factor beta2.Si yo tengo un vector de maturity de 77 datos, la pregunta es:¿Qué tan importante es el argumento MidTau, y qué otra especificación tiene? no me queda muy claro cómo

Hi R fans I am trying to make a program to ask the user to choose data file: print("Choose data file please !") matr=read.table(file.choose(),dec=".",header=TRUE) The problem is that the prompt Choose data file please ! comes after I have chosen the file. What am doing wrong? Thanks in advance Ralf Finne

> Tukey divides the points into three groups, not the x and y values separately. > I'll try to get hold of the book for a direct quote, might take a couple of days. Ah well, I can't get it for a week. But the fact that it's often called Tukey's three group line (try a search on *tukey three group line* and you'll get plenty of hits) is pretty much a giveaway. On Mon,

Hello, I am really new to R and it's still a challenge to me. Currently I'm working on my Master's Thesis. My supervisor works with SAS and is not familiar with R at all. I want to run an Anova, a tukey-test and as a result I want to have the tukey-grouping ( something like A - AB - B) I came across the HSD.test in the agricolae-package, but... unfortunately I do not get an output

Hi everyone I'm using Tukey HSD as post-hoc test following a lme analysis. I'm measuring hemicelluloses in different species treated with three different CO2 concentrations (l=low, m=medium, h=high). The whole experiment is a split-plot design and the Tukey-function from the package multcomp is suitable for lme-analysis with random factors. The analysis works fine but I get a non

Hello, I am trying to determine the most appropriate way to run post-hoc comparisons on my lme model. I had originally planned to use Tukey HSD method as I am interested in all possible comparisons between my treatment levels. TukeyHSD, however, does not work with lme. The only other code that I was able to find, and which also seems to be widely used, is glht specified with Tukey:

Hi, I need to determinate HSD value from a matrix like that Thesis Days A1 Cx 0 66.07 Cx 0 60.24 Cx 0 42.86 Tw 0 66.07 Tw 0 60.24 Tw 0 42.86 Aa 0 66.07 Aa 0 60.24 Aa 0 42.86 Qe 0 66.07 Qe 0 60.24 Qe 0 42.86 Cx 56 310.86 Cx 56 223.17 Cx 56 186.77 Tw 56 149.42 Tw 56 127.75 Tw 56 138.59 Aa 56 130.24 Aa 56 214.83 Aa 56 137.95 Qe 56 186.64 Qe 56 189.09 Qe 56 187.87 this is my script

The problem or actual R implementation relies on an assumption that median(x[i] | x[i] <= quantile(x, 1/3)) == quantile(x, 1/6) which reveals not to be true despite very trustful appearance. If we continue with the example of x=y=1:9 then quantile(x, 1/6)=2.5 (here quantile() is taken in C-code sens, not R's one) while median(y[i] | x[i] <= quantile(x, 1/3))=2 On the other sample's

I'm using SAS for my statistical purpose and I'm triyng to jump in the R' world. How can i implement Tukey linear test in R? In sas-code my lines are : PROC GLM; BY PARCELLA; CLASS TESI; MODEL PROD=TESI; MEANS TESI/TUKEY lines; IN R: ab<-type.convert(a$tesi) a<-cbind(a,ab) cc<-anova(lm(prod~ab,data=a)) cc2<-aov(prod~ab,data=a) tt<-TukeyHSD(cc2,ordered=TRUE) but how can

Dear R users; I am modelling densities of some species of birds, so I have a problem with a great ammount of zeros. I have decided to try GLMs with the tweedie family, but in all the models I have tried I got an NA for the AIC value. Just to check the problem I've compared the a glm using the Gaussian family with the identity link and a glm using the tweedie family with var.power=0 and

I have been trying to do tukey's test to no avail. This is what I have and the error produced: pen.df = data.frame(blend, treatment, y) source("tukey.1.r") tukey.1(aov.pen, pen.df) Error in tukey.1(aov.pen, pen.df) : the model must be two-way This is a two-way design. Therefore I am confused. Can anyone help? Raphael > pen.df blend treatment y 1 1 A 89 2

Sorry, I have seen it too late that we had different tab width in the original file and my editor. Here is the patch with all white spaces instead of mixing tabs and white spaces. Serguei. Le 29/05/2017 ? 15:13, Serguei Sokol a ?crit : > Here is an attached patch. > > Best, > Serguei. > > Le 29/05/2017 ? 12:21, Serguei Sokol a ?crit : >> The problem or actual R

And with "equally spaced" I obviously meant "of equal size". It's getting too hot in the office here... On Wed, May 31, 2017 at 4:39 PM, Joris Meys <jorismeys at gmail.com> wrote: > Seriously, if a method gives a wrong result, it's wrong. line() does NOT > implement the algorithm of Tukey, even not after the patch. We're not > discussing Excel here,