similar to: Re: suggestion on data mining book using R

Hi Thomas, see these papers or books (some are available on the web): Diego Kuonen, Introduction au data mining avec R : vers la reconqu??te du `knowledge discovery in databases' par les statisticiens. Bulletin of the Swiss Statistical Society, 40:3-7, 2001. Consultabile all??indirizzo web: http://www.statoo.com/en/publications/2001.R.SSS.40/ Diego Kuonen and Reinhard Furrer, Data mining

Dear R-user, I wish to know if someone is using R as concern Datamining or KDD (Knowledge Discovery in Database) and if already exists a R package specialized in this kind of analysis. I found this contributes on the R web site: [20] Diego Kuonen. Introduction au data mining avec R : vers la reconqu??te du `knowledge discovery in databases' par les statisticiens. Bulletin of the Swiss

R people, I need to know if is possible to make data mining with R. If so, is there any manual or somewhere/one to consult about that. Thank you very much Adri?n

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

Hi, how can I import really big plain text data files (several GB) from an ERP-System (SAP-Tables) to R? The Header of these files are always similar, for example: Tabelle: T009 Angezeigte Felder: 7 von 7 Feststehende F??hrungsspalten: 2 Listbreite 0250 ---------------------------------------------------------------------- |X|MANDT|PERIV|XKALE|XJABH|ANZBP|ANZSP|LTEXT

Deall all, We need to perform a statistical analysis of a large database (40,000 entries with approximately 500 fields in each entry) currently handled in Oracle. The data contains categorical variables only. At the current stage we suggest classification and clustering analysis. We are planning to perform the analysis in R and would be very grateful for any

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

Hi, see ?cor in base package to get correlation matrix for your data. Maybe it could be usefull getting principal components (give a look to: ? princomp (base)) to reduce the number of variables. Hoping I helped you. Best regards, Vito You wrote: Hi all: I have a question on how to go about creating a correlation matrix. I have a huge amount of data....21 variables for 3471 times. I want

Hi, did you see: as.data.frame() as.matrix() as.vector() matrix() > x a b c 1 1 2 3 2 1 2 3 3 2 3 4 4 3 4 5 > is.data.frame(x) [1] TRUE > as.matrix(x) a b c 1 1 2 3 2 1 2 3 3 2 3 4 4 3 4 5 > y<-as.matrix(x) > is.matrix(y) [1] TRUE > as.vector(y) [1] 1 1 2 3 2 2 3 4 3 3 4 5 > z<-as.vector(y) > m<-matrix(z,ncol=3) > m [,1] [,2] [,3] [1,] 1 2

Hi, Attention chi-squared distribution, unlike F distribution, has only df1 as parameter, not df1 and df2. So correct into: outer(1:3, 1:3, function(df1, df2) qchisq(0.95, df1, df2)) outer(1:3, 1:3, function(df1, df2) qchisq(0.95, df1)) ^^^^^^^^^^^^^^^^^^^^ Regards, Vito you wrote: Dear Rs: outer(1:3, 1:3, function(df1, df2) qf(0.95, df1, df2)) I compare this F

Hi, pchisq -> distribution function dchisq -> density function pval is the area under the curve, to calculte it you use distribution function which is the integral of density function. See: http://www.itl.nist.gov/div898/handbook/eda/section3/eda362.htm http://mathworld.wolfram.com/DistributionFunction.html f(x) density function F(x) distribution function =Pr(X<x)= integral(f(x))

See: http://wwwpeople.unil.ch/jean-pierre.mueller/ ttda - tools for textual data analysis Regards Vito you wrote: Hi, Does a text miner exist in R-language similar to Splus miner or SAS text miner? I would appreciate any information. TIA, Aldi ===== Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the scientific

Dear UseRs, I'm glad to inform that an English version of my contribute concerning fitting distributions is now available on CRAN: http://cran.r-project.org/doc/contrib/Ricci-distributions-en.pdf Any comments will be appreciated. Best regards, Vito ===== Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the

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

Hi, I found this document, but it concerns S+. If it could interest you'll see: http://faculty.washington.edu/ezivot/book/QuanCopula.pdf Cordially Vito You wrote: Dear R: Is there a function or a reference to simulate Gumbel copulas, please? Thanks in advance! Sincerely, Erin Hodgess mailto: hodgess at gator.uhd.edu R version 2.0.1 windows ===== Diventare costruttori di soluzioni

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

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've a list containing parameters (intercepts & coefficients) of 12 regressions fitted > coeff [[1]] (Intercept) anno -427017.1740 217.0588 [[2]] (Intercept) anno -39625.82146 21.78025 ..... [[12]] (Intercept) anno 257605.0343 -129.7646 I want create a data frame with two columns (intercept and anno)using data in these list. Any help

Hi, I suggest to give a look to: ?Practical Regression and Anova using R? by Julian Faraway http://cran.r-project.org/doc/contrib/Faraway-PRA.pdf http://www.stat.lsa.umich.edu/~faraway/book/ see also package faraway for datasets: http://cbio.uct.ac.za/CRAN/src/contrib/Descriptions/faraway.html for some econometric data sets: http://www.oswego.edu/~kane/econometrics/data.htm for data sets: